Kiranbir, we’re delighted to have you at AITech Park, could you please share your professional journey with us, highlighting key milestones that led you to your current role as a Senior Staff Engineering Manager at Google?

I started as a software engineer at Garmin then Apple. As I grew my career at Apple, I wanted to help and lead my peers the way my mentors helped me. I also had an arrogant epiphany about how much more I could get done if I had a team of people just like me. That led to my first management role at Microsoft.

Initially, I found it challenging to balance my desire to have my team work my way with prioritizing their career growth. Eventually, I was responsible for a program where I had to design, develop, and ship an accessory for the Hololens in only six months. I was forced to delegate and let go of specific aspects and realized I was getting in the way of progress. 

My team was delivering amazing solutions I never would have thought of. I realized I didn’t need to build a team in my image. I had hired a talented team with unique skills. My job now was to empower them and get out of their way. This realization was eye-opening and humbled me.

I also realized the skills I used for engineering weren’t the same skills I needed to be an effective leader. So I started focusing on being a good manager. I learned from even more mistakes over the years and ultimately established three core values for every team I lead:

1. Trust your team and peers, and give them autonomy.
2. Provide equity in opportunity. Everyone deserves a chance to learn and grow.
3. Be humble.

Following my growth as a manager, Microsoft presented me with several challenges and opportunities to help struggling teams. These teams moved into my organization after facing cultural setbacks, program cancellations, or bad management. Through listening, building psychological safety, providing opportunities, identifying future leaders, and refusing egos, I helped turn them around. 

Helping teams become self-sufficient has defined my goals and career in senior management. That led to opportunities at Google where I could use those skills and my engineering experience.

In what ways have you personally navigated the intersection of diversity, equity, and inclusion (DEI) with technology throughout your career?

Personally, as a Sikh, I rarely see people who look like me in my city, let alone in my industry.  At times, I have felt alone. I’ve asked myself, what will colleagues think and see the first time we meet?

I’ve been aware of representing my community well, so nobody holds a bias against those who come after me. I feel the need to prove my community, not just myself, while feeling grateful for the Sikhs who broke barriers, so I didn’t have to be the first. When I started looking for internships, I considered changing my name. When I first worked on the Hololens, I couldn’t wear it over my turban.

These experiences led me to want to create a representative workplace that focuses on what you can do rather than what you look like or where you came from. A workplace that lets you be your authentic self. A workplace where you create products for everyone.

Given your experience, what personal strategies or approaches have you found effective in promoting diversity within tech teams and ensuring equitable outcomes?

One lesson I received early in my career in ensuring our recruiting pipeline was more representative was patience. One of my former general managers shared a statistic or a rule of halves:

• 32 applications submitted
• 16 resumes reviewed by the hiring manager
• 8 candidates interviewed over an initial phone screen
• 4 candidates in final onsite interviews
• 2 offers given
• 1 offer accepted

His point was that if you review applications in order, you will likely find a suitable candidate in the first thirty applications. To ensure you have a representative pipeline, you have to leave the role open to accept more applications, and you get to decide which applications to review first. 

Additionally, when creating job requisitions, prioritize what’s important for the company and not just the job. What are the skills and requirements in the long term? What skills are only necessary for the short term? I like to say, don’t just hire the best person for the job today, hire the best person for the team for the next five years. Try to screen in instead of screening out.

To ensure equitable outcomes, I point to my second leadership value, equity in opportunity. The reality of any team is that there might be limited high-visibility opportunities at any given time. For my teams, no matter how well someone delivered in the past, the next opportunity and challenge are given to someone else. Even if others might complete it faster, everyone deserves a chance to learn and grow. 

Moreover, we can focus on moving far, not just fast, when everyone grows. When this is practiced and rewarded, teams often find themselves being patient and supporting those currently leading efforts. While I don’t fault individuals who disagree, their growth isn’t more important than the team’s.

From your perspective, what advice would you offer to tech leaders and organizations looking to strengthen their DEI initiatives, particularly in the context of developing and deploying AI technologies?

My first advice for any DEI initiative is to be patient. You won’t see changes in one day, so you want to focus on seeing changes over time. That means not giving up early, with leaders providing their teams more time to recruit and interview rather than threatening position clawbacks if the vacancy isn’t filled.

Ultimately, AI models are only as good as the data they are trained on. Leaders need to think about the quality of the data. Do they have enough? Is there bias? Is there data that might help remove human biases? 

How do biased AI models perpetuate diversity disparities in hiring processes, and what role do diverse perspectives play in mitigating these biases in AI development?

Companies that already lack representation risk training their AI models on the skewed data of their current workforce. For example, among several outlets, Harvard Business Review has reported that women might only apply to a job if they have 100% of the required skills compared to men who apply when they meet just 60% of the skills. Suppose a company’s model was built on the skills and qualifications of their existing employees, some of which might not even be relevant to the role. In that case, it might discourage or screen out qualified candidates who don’t possess the same skillset.

Organizations should absolutely use data from current top performers but should be careful not to include irrelevant data. For example, how employees answer specific interview questions and perform actual work-related tasks is more relevant than their alma mater. They can fine-tune this model to give extra weight to data for underrepresented high performers in their organization. This change will open up the pipeline to a much broader population because the model looks at the skills that matter.

In your view, how can AI technologies be leveraged to enhance, rather than hinder, diversity and inclusion efforts within tech organizations?

Many organizations already have inherent familiarity biases. For example, they might prefer recruiting from the same universities or companies year after year. While it’s important to acknowledge that bias, it’s also important to remember that recruiting is challenging and competitive, and those avenues have likely consistently yielded candidates with less effort.

However, if organizations want to recruit better candidates, it makes sense to broaden their recruiting pool and leverage AI to make this more efficient. Traditionally, broadening the pool meant more effort in selecting a good candidate. But if you step back and focus on the skills that matter, you can develop various models to make recruiting easier. 

For example, biasing the model towards the traditional schools you recruit from doesn’t provide new value. However, if you collect data on successful employees and how they operate and solve problems, you could develop a model that helps interview candidates to determine their relevant skills. This doesn’t just help open doors to new candidates and create new pipelines, but strengthens the quality of recruiting from existing pipelines.

Then again, reinforcing the same skills could remove candidates with unique talent and out-of-the-box ideas that your organization doesn’t know it needs yet. The strategy above doesn’t necessarily promote diversity in thought.

As with any model, one must be careful to really know and understand what problem you’re solving and what success looks like, and that must be without bias.

In what specific ways do you believe AI can be utilized to identify and address systemic barriers to gender equality and diversity in tech careers?

When we know what data to collect and what data matters, we understand where we introduce bias, place less effort, and miss gaps. For example, the HBR study I shared that indicated women needed 100% of the skills to apply also debunked the idea that confidence was the deciding factor. Men and women cited confidence as the reason not to apply equally. The reality was that people needed to familiarize themselves with the hiring process and what skills were considered. So our understanding and biases come into play even when trying to remove bias!

An example I often use for AI is medical imaging. A radiologist regularly looks at MRIs. However, their ability to detect an anomaly could be affected by multiple factors. Are they distracted or tired? Are they in a rush? While AI models may have other issues, they aren’t susceptible to these factors. Moreover, continuous training of AI models means revisiting previous images and diagnoses to improve further because time isn’t a limitation. 

I share this example because humans make mistakes and form biases. Our judgment can be clouded on a specific day. If we focus on ensuring these models don’t inherit our biases, then we remove human judgment and error from the equation. This will ideally lead to hiring the mythical “best” candidate objectively and not subjectively.

As we conclude, what are your thoughts on the future of AI in relation to diversity and inclusion efforts within the tech sector? What key trends or developments do you foresee in the coming years?

I am optimistic that a broader population will have access to opportunities that focus on their skills and abilities versus their background and that there will be less bias when evaluating those skills. At the same time, I predict a bumpy road. 

Teams will need to reevaluate what’s important to perform the job and what’s helpful for the company, and that’s not always easy to do without bias. My hope is that in an economy of urgency, we are patient in how we approach improving representation and that we are willing to iterate rather than give up.

Kiranbir Sodhia

Senior Staff Engineering Manager at Google

Kiranbir Sodhia, a distinguished leader and engineer in Silicon Valley, California, has spent over 15 years at the cutting edge of AI, AR, gaming, mobile app, and semiconductor industries. His expertise extends beyond product innovation to transforming tech teams within top companies. At Microsoft, he revitalized two key organizations, consistently achieving top workgroup health scores from 2017 to 2022, and similarly turned around two teams at Google, where he also successfully mentored leaders for succession. Kiranbir ‘s leadership is characterized by a focus on fixing cultural issues, nurturing talent, and fostering strategic independence, with a mission to empower teams to operate independently and thrive. Kiranbir Sodhia: Transforming Tech Teams; Cultivating Leaders

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SandboxAQ today announced a technology collaboration with Mayo Clinic to explore the use of advanced, AI-powered magnetocardiography (MCG) technology with the goal of radically improving cardiac diagnostics. The collaboration marks a significant step forward in the global fight against cardiovascular diseases, which remain one of the leading causes of death worldwide, claiming millions of lives every year.

As part of the collaboration, Mayo Clinic researchers will test SandboxAQ’s novel MCG imaging system, called CardiAQ, powered by state-of-the-art magnetic sensors and advanced AI algorithms. This mobile, non-invasive, non-contact cardiac imaging device will enable rapid and radiation-free visualization and assessment of the magnetic signals of the heart. The initial phase of the collaboration will be a clinical research study to examine the relationship between MCG and the findings seen in angiography. The study will take place throughout 2024 and 2025 at the Mayo Clinic in Rochester, MN.

“This collaboration between Mayo Clinic and SandboxAQ will further this breakthrough MCG technology for cardiac diagnostics.  Cardiac disease is the leading cause of death globally and novel methods to easily and accurately diagnose disease are urgently needed,” said Kit Yee Au-Yeung, Director of SandboxAQ’s medical devices division. “CardiAQ captures detailed data from the heart, which could lead to faster, more accurate diagnoses and fill in the gap between low-cost EKG or biomarker tests and high-cost CT scans or invasive angiography.”

CardiAQ will look to address the need for faster, more accurate and accessible medical imaging technologies. The system leverages high performance sensors to measure minute variations in the magnetic field around the human heart, and advanced quantitative AI algorithms that can eliminate electromagnetic interference in a dynamic hospital environment. By capturing more pristine electrical conduction activities in every heartbeat, doctors may be able to better detect abnormal patterns and uncover other indicators about potential cardiac disease states.

Building upon successful clinical studies at UCSF Medical Center and New York’s Mount Sinai West medical center, CardiAQ delivers key benefits including:

• Requires no purpose-built space
• Mobile for point-of-care use
• Requires no cooling or shielding to operate
• Measurement takes minutes to complete

For more information about SandboxAQ’s MCG device, please visit https://www.sandboxaq.com/sensing

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Zscale Labs is excited to announce the launch of its revolutionary Neuromorphic AI, a state-of-the-art tool designed to advance medical diagnostics by enabling multi-label Chest X-Ray image classification. This breakthrough technology demonstrates how Zscale Labs is reshaping the landscape of healthcare through cognitive computing.

Accurate and timely diagnosis is critical, particularly for respiratory conditions. Our innovative tool leverages the power of Zscale Labs Hyperdimensional Computing (HDC) and deep learning to assist radiologists and healthcare providers in diagnosing multiple chest conditions from X-ray images. This ensures better patient outcomes and underscores the transformative potential of AI in precision medicine.

Key features of our Neuromorphic AI breakthrough include:

• Advanced Spatial Transformer Network (STN): Enhances the precision of image analysis by focusing on relevant areas within X-rays.
• Hyperdimensional Computing (HDC) Encoding: Operates in a high-dimensional space for superior pattern recognition and accurate multi-label classification.

Zscale Labs brain-inspired approach empowers medical professionals with intricate details crucial for precise diagnosis, operating efficiently in high-dimensional spaces to enhance pattern cognition. This technology not only improves diagnostic accuracy but also significantly reduces analysis time, making it an invaluable tool in modern healthcare.

For more information about Zscale Labs and its Neuromorphic AI technology, visit
https://www.zscalelabs.com/post/revolutionizing-healthcare-with-neuromorphic-ai

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Avicenna.AI, a leading medical imaging AI company, has received Medical Device Regulation (MDR) certificate for five of its algorithms from certification body BSI Medical Devices. This development means the company’s product portfolio is fully compliant with the European Union’s MDR 2017/745, which is now mandatory for medical device companies that want to provide their solutions in Europe.

The MDR was introduced to update the EU’s regulations for medical devices, addressing safety issues and the recent emergence of AI tools and software as a medical device (SaMD), which did not exist when the old regulations were created. Ensuring MDR compliance is a critical component of obtaining and maintaining CE-mark status, which allows a device to be freely traded in the EU.

Compared to the previous Medical Device Directive (MDD), the MDR has a wider scope and more stringent requirements. It emphasizes clinical evaluation, post-market surveillance, device traceability, rigorous technical documentation, and risk management. These measures aim to enhance patient safety and ensure high standards for medical devices, including AI and software-based solutions.

Avicenna.AI’s products have been certified as Class IIb medical devices, which requires a high level of clinical validation. The certified products include the company’s suite of AI tools for neurovascular conditions, as well as its suite of algorithms for vascular conditions.

“Obtaining MDR certification is a significant milestone for Avicenna.AI,” said Stéphane Berger, Regulatory Manager at Avicenna.AI. “It demonstrates our commitment to meeting the highest standards of medical device safety and performance. This certification not only reinforces our dedication to compliance but also assures our customers of the quality and reliability of our AI product portfolio.”

The company’s MDR-certified AI tools include algorithms for intracranial hemorrhage (CINA-ICH), large vessel occlusion (CINA-LVO), quantification of stroke severity (CINA-ASPECTS), aortic dissection (CINA-AD), pulmonary embolism (CINA-PE), and opportunistic cases of pulmonary embolism (CINA-iPE). All the products are also CE-marked and FDA-cleared.

“Crucially, despite the differences in SaMD regulatory requirements between authorities in the US and Europe, we are consistently achieving both FDA and CE mark clearance for our AI products,” added Berger.

All of Avicenna.AI’s AI tools are seamlessly integrated into radiologists’ clinical workflow, automatically triggering and reporting algorithm results through the systems already used by radiologists.

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United Imaging, a global leader in manufacturing advanced medical imaging and radiotherapy equipment, will unveil its latest MRI technology, boasting incredible advancements across various fronts, as a Gold sponsor at this year’s ISMRM meeting.

The company’s exhibit at this year’s ISMRM meeting strategically divides into four sections: Ultra-High Field, Ultra-High Gradient, Artificial Intelligence, and Innovation Community. Each section addresses industry priorities and showcases sophisticated technological advancements.

“United Imaging has always been dedicated to pushing boundaries and driving innovation,” says Dr. Al Zhang, Ph.D, Chairman & Co-CEO. “ISMRM holds immense value for us, fostering connections with global partners who share our drive for progress. Our purposeful innovation drives scientific research forward, leading to groundbreaking advancements in healthcare technology. Guided by our mission, ‘Equal Healthcare for All,’ we remain committed to pioneering solutions that enhance patient care worldwide.”

At the forefront of the “Ultra-High Field” showcase is the uMR Jupiter 5T, a revolutionary whole-body 5T MRI system that recently received FDA clearance. It transcends the traditional constraints of ultra-high-field MRI, previously confined to imaging of the brain and selected MSK joints. The potential applications of the uMR Jupiter 5T extend to encompass the abdomen, heart, pelvis, and additional anatomical regions. uMR Jupiter has the potential to eclipse the capabilities of standard 3T MRI machines in resolution and signal-to-noise ratio, delivering clarity that empowers radiologists to uncover clinical details previously hidden, truly allowing them to ‘see the unseen.’ The uMR Jupiter 5T is also designed to overcome the key hurdles of ultra-high-field MRI: image uniformity and radio frequency safety. It fits into existing 3T MRI spaces, signaling a significant advancement in the industry.

Highlighted also in the “Ultra-High-Field” section is the “SuperFlexFree Coils” (not available in the U.S. or EU for commercial or clinical use). There are three types of coils in this set and all are 24 channels. Each is designed for scanning large joints and the heart, small joints, and delicate structures respectively. Compared to traditional coils, SuperFlexFree Coils have a significantly higher coil density and flexibility, which will result in better image signal-to-noise ratio and acceleration performance.

Additionally, United Imaging introduces breakthroughs in the “Ultra High Gradient” category, including the uMR Sagitta (not submitted to the FDA; not available in the U.S. for commercial or clinical use) and the uMR NX Frontier (not submitted to the FDA; not available in the U.S. for commercial or clinical use). uMR Sagitta completely revolutionizes the performance limits of magnetic resonance, achieving significant advances in global research in 3T systems. With the powerful ‘Twin-Engine technology’ driving force, its gradient performance surpasses 240 mT/m and 200 T/m/s, offering a fresh perspective in precise diagnosis and treatment. uMR NX Frontier (not submitted to the FDA; not available in the U.S. for commercial or clinical use), dedicated to brain research, serves as the new-gen model of Human Connectome Project (HCP) studies, boasting ultra-high-performance gradients of 650 mT/m and 600 T/m/s, leading a frontier exploration in neuroscience.

For the “Artificial Intelligence” section, United Imaging highlights the uAIFI Technology Platform, an innovative end-to-end technology platform that revolutionizes MRI through AI-integrated hardware and software. It significantly enhances image quality, expedites diagnostic processes and improves user-friendliness, pioneering advances in patient care. This holistic approach spans the care continuum, with standout features like ACS, an AI-assisted MR acceleration technology for enhanced 2D and 3D imaging. This platform evolved intelligently, bringing a new level of AI integration to uMR systems.

United Imaging has always been dedicated to advancing MRI research through collaboration with industry partners. The ADEPT platform – Application Developing Environment and Programming Tools — is a comprehensive platform offering essential features of precise hardware control and effortless application development. Coupled with extensive support for research platform interfacing and a vibrant scientific community, ADEPT marks a significant leap forward in accelerating user development and advancing scientific research in the field of MRI.

ISMRM attendees are invited to experience the future of MRI at Booth A18.

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PocketHealth, the leader in patient-centric medical image exchange, today announced it has raised $33 million USD ($45 million CAD) in Series B funding. The all-equity round was led by Round13 Capital with participation from Deloitte Ventures, Samsung Next, and existing investors Questa Capital and Radical Ventures.

The funding will enable PocketHealth to continue to evolve how medical images are shared, leverage AI to personalize the patient’s care journey, and grow its footprint across the US and Canada. To support these goals, the company plans to double its workforce over the next two years.

PocketHealth was founded in 2016 by brothers Harsh and Rishi Nayyar to give patients access, control, and a deeper understanding of their health records while streamlining the way healthcare providers share medical imaging.

“Medical imaging is the spark to nearly every patient journey, yet manual and legacy image sharing systems deemphasize patient access to their own data, generating unnecessary costs, and delaying patient care,” said Rishi Nayyar, Co-Founder and CEO, PocketHealth. “We’ve proven that when patients gain access to diagnostic-quality imaging and our industry-leading AI helps them understand their records, they are empowered to advocate for their care. The end result is increased patient satisfaction, a faster image sharing process for providers, and greater patient retention. Now, our goal is to make PocketHealth accessible to every patient at every provider across North America.”

With PocketHealth, providers gain a secure, next-generation platform for easily exchanging diagnostic images with both patients and external providers. Uniquely, PocketHealth customers have the flexibility to instantly share images with anyone, across any network — or set up a local network of PocketHealth Community Gateways for automated image exchange. This ensures that records get where they need to, instead of relying on a CD-ROM, return visits to the hospital, or a broken portal experience, which disrupts the patient’s care journey.

The platform uses AI to provide patients with personalized insights and improved understanding of their health. Report Reader explains medical terms in the patient’s report, Follow-Up Navigator intelligently detects follow-up imaging recommendations — encouraging patients to return for new imaging on-schedule — and MyCare Navigator equips patients with relevant, personalized questions to ask their doctor. As a result, 87% of patients surveyed say they are more likely to return to the same healthcare provider when they have access to their imaging through PocketHealth.

“For 20 years, medical image exchange has meant moving files across a closed network, from point A to point B,” said Nayyar. “We’re now seeing some of the largest health systems in North America expecting more from their image exchange and adopting PocketHealth to drive patient retention, satisfaction, and finally solve their image exchange needs.”

PocketHealth connected sites have seen improved patient experience, operational efficiencies, and cost savings.

• Colorado’s Valley View Hospital reduced non-labor costs associated with burning CDs by 95% and enabled patient and staff image sharing with out-of-network providers.
• Toronto’s Unity Health gained more than $120,000 in annual savings and closed their imaging library.

“PocketHealth is tackling a massive problem that requires the ability to build a thoughtful, resilient product experience for patients, physicians, and the most complex healthcare providers,” said Brahm Klar, Managing Partner, Round13 Capital. “We are impressed with how effectively the PocketHealth team has been able to rise to this challenge and create a solution that ensures data gets where it needs to go, instantly, empowering patients along the way. We are thrilled to join PocketHealth on this journey, and look forward to this exciting next stage of growth.”

Over its eight-year journey, PocketHealth has secured contracts with major health systems and outpatient imaging groups across North America including University Health Network, Southern Illinois Healthcare, UofL Health, Universal Health Services, Radiology Partners, and more. With this funding, the company has raised over $55.5 million USD ($75 million CAD) in equity to date. Miranda Ferris, Principal at Round13 Capital, will join the PocketHealth Board.

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Coreline Soft, a pioneer in medical artificial intelligence (AI) imaging, unveils cutting-edge AI medical imaging solutions at the ECR 2024 (European Congress of Radiology), establishing a new standard for healthcare across Europe. ECR, the largest radiology conference in Europe, attracts global experts and medical device industry professionals.

Coreline Soft is set to make a mark at the ECR 2024 by presenting its AVIEW product line. The exhibition will feature demonstrations of AVIEW LCS Plus for simultaneous diagnosis of chest diseases, AVIEW COPD for automatic analysis of chronic obstructive pulmonary disease, and AVIEW RT ACS, an AI-based fully automated contouring solution.

The showcase will encompass a comprehensive range of products from screening and diagnosis to treatment and management. Highlighting the AVIEW LCS Plus, capable of screening three major pulmonary conditions in CT scans, the presentation will focus on real-world applications in hospitals worldwide. The company will share insights into the benefits for medical professionals, workflow improvements, and enhanced diagnostic efficiency.

Coreline Soft has been actively expanding its presence in Europe, securing projects such as the multinational lung cancer screening initiative (iDNA) involving five European countries. Projects like the HANSE lung cancer screening in Germany and the ILSP lung cancer screening in Italy, led by the prestigious National Cancer Institute in Milan with 18 participating hospitals and cancer centers, showcase the company’s competitiveness in the global lung cancer screening market.

Having recently signed supply agreements with renowned institutions such as Heidelberg University Hospital in Germany, Catania University Hospital in Italy, and the large imaging center group ImaGen in France, Coreline Soft is poised to further extend its footprint in the European healthcare market.

Jason Seo, Director of Overseas Business Development at Coreline Soft, said, “We have accumulated expertise in entering local hospitals and national-level projects, positioning the European market as a forward base for the global market.”

Coreline Soft continues to strengthen its global presence, offering innovative AI solutions to advance healthcare practices in Europe and beyond.

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To read the US and global reports, visit: 
https://klasresearch.com/report/2024-best-in-klas-awards-software-and-services/3413
https://klasresearch.com/report/2024-best-in-klas-awards-global-software/3414

“These awards showcase our excellent employees who continuously go above and beyond to meet customer needs. Over the past year, we have restructured our organization into teams to ensure consistent and knowledgeable guidance throughout the sales, implementation, and support phases of the customer journey. This, along with product offerings that reduce IT costs, increase security, and grow with our users’ enterprise imaging requirements, has solidified our success,” says Marie Ekström Trägårdh, Executive Vice President Sectra AB and President Sectra Imaging IT Solutions.

Sectra 2024 Best in KLAS honors include US Large PACS, US Small PACS, PACS Global (Canada), PACS Global (Northern Europe), and PACS Global (Southern Europe). 

The first Sectra PACS installation was in Sweden in 1993, and now, the company has more than 2,500 sites worldwide. The radiology module is an integral part of Sectra’s enterprise imaging solution, also comprising VNA and imaging modules for cardiology, orthopedics, ophthalmology, and digital pathology in one single system.

Adam Gale, CEO of KLAS shared his thoughts for the 2024 winners:
“At KLAS, we firmly believe that the voice of healthcare providers and payers is paramount. The Best in KLAS awards are based on extensive feedback and evaluations from healthcare professionals across the nation. Winning a Best in KLAS award, therefore, is not just about recognition; it shows the trust and confidence that healthcare providers place in the winning vendors. It also helps validate each vendor’s commitment to innovation, quality, and customer satisfaction. We are proud to recognize 2024’s Best in KLAS award winners! Their unwavering dedication to improving patient outcomes is wonderfully inspiring.” 

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Intelerad Medical Systems, a global leader in medical imaging software solutions, was recognized as a 2024 Best in KLAS: Global Software Report award winner. The company has earned its recognition as the 2024 Best in KLAS vendor for the UK and Ireland PACS, leading the category across both regions based on provider and payers’ feedback in 2023.

Intelerad’s InSight PACS is a tailor-made PACS solution that has been adopted by over 250 healthcare providers across the UK and Ireland. The technology features a single, powerful interface for all users, and offers advanced functionality that delivers key clinical benefits such as advanced regional image sharing and MDT support, home reporting and teleradiology, and seamless integration with AI algorithms. The innovative PACS offering is a critical resource for UK healthcare professionals, who are facing an ageing and growing population, and a shortage of radiologists in addition to challenges around costs of healthcare.

“The demand for better technology that can drive essential workflow efficiencies for healthcare providers and help solve industry issues is greater than ever. Intelerad’s InSight PACS is a solution that is built and refined by UK professionals for UK clinicians who understand the needs and challenges standing in the way of better care outcomes,” said Morris Panner, President, Intelerad. “Receiving this recognition by KLAS as the number one leader in UK and Ireland PACS for 2024 is an incredible honour, and we will continue investing in this critical technology to better serve healthcare providers and the patients they serve.”

As the most comprehensive report of its kind in the healthcare IT industry, the annual 2024 Best in KLAS: Global Software Report recognizes vendors for their outstanding efforts to help healthcare professionals deliver better patient care. Using KLAS’ research process and methodology, all rankings are a direct result of the feedback from thousands of providers over the last year. A Best in KLAS award determines the standard of excellence that the top vendors should provide in a partnership.

“At KLAS, we firmly believe that the voice of healthcare providers and payers is paramount. The Best in KLAS awards are based on extensive feedback and evaluations from healthcare professionals across the nation. Winning a Best in KLAS award, therefore, is not just about recognition; it shows the trust and confidence that healthcare providers place in the winning vendors,” said Adam Gale, CEO, KLAS Research. “It also helps validate each vendor’s commitment to innovation, quality, and customer satisfaction. We are proud to recognize 2024’s Best in KLAS award winners! Their unwavering dedication to improving patient outcomes is wonderfully inspiring.”

A sample of feedback from the providers who use Intelerad’s InSight PACS and participated* in the KLAS research process is included below.

“The vendor has good customer support in the UK. The product is reliable with very few, if any, unplanned instances of downtime. The product is easy to use.” – Manager, September 2023

“The vendor’s biggest strengths and the things we like most are the desktop support and the trainer knowledge and that the network team is all very knowledgeable. InSight PACS and our other PACS work well together and are reliable. The Intelerad system is adequate for breast screening images, and it manages tomosynthesis images well and is easy to use. The consultants are happy with the product when reading images.” – Manager, September 2023

“InSight PACS Is a user-friendly product, and the vendor has an excellent support team for when something isn’t working properly.” – Manager, September 2023
*Selected commentary collected about Intelerad’s InSight PACS © 2023 KLAS. Visit klasresearch.com for a complete view.

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Visage Imaging, Inc. (“Visage”), a wholly owned subsidiary of Pro Medicus Ltd. (ASX: PME), has announced the launch of the groundbreaking Visage Ease VP for Apple Vision Pro, Apple’s highly anticipated spatial computing platform released today.

Designed to take advantage of the unique capabilities of Apple Vision Pro, Visage Ease VP supports immersive, spatial experiences for diagnostic imaging and multimedia. Visage Ease VP includes all the proven functionality of Visage Ease, plus the exciting addition of Visage’s powerful cinematic rendering engine for stunning volume-rendered images in immersive space. Anywhere, on-the-go access with Visage Ease VP has additional flexibility with virtual screens at more than 4K resolution per eye, the independence from environmental lighting restrictions, and the ability to interact with imaging seamlessly in your physical space. Visage Ease VP uses the natural and intuitive input of eyes, hands, and voice navigation to provide an end-user imaging experience that’s magical and unlike any other application.

UC San Diego Health is the first health system to pilot the technology. “The visualization of three-dimensional medical imaging in immersive space creates exciting opportunities to improve patient care,” said Dr. Paul Murphy, associate clinical professor at UC San Diego School of Medicine and radiologist at UC San Diego Health. “Technology that allows for sophisticated eye motion and gesture controls for reviewing 2D and 3D medical imaging could potentially help in efficient tumor board reviews and create collaborative spaces in healthcare.”

Today’s launch of Visage Ease VP signals just the beginning and ushers in a new era of spatial imaging and workflow possibilities.

“Visage’s platform of enterprise imaging applications that support the Apple ecosystem are used by many of the world’s largest, most sophisticated healthcare organizations, and also integrated bi-directionally to the most widely used EHR,” said Malte Westerhoff, PhD, Visage co-founder and global chief technology officer.

Visage Ease VP (visionOS) is the latest member of the Visage Ease family of native apps purpose-built for the Apple ecosystem, joining Visage Ease (iOS/iPadOS) and Visage Ease Pro (iPadOS). Visage also offers the acclaimed Visage 7 smart-client application for macOS, providing native, ultrafast, clinically rich, highly interoperable access to enterprise imaging.

Visage Ease VP is exclusively intended for use by Visage customers on the industry-leading Visage^® 7 Enterprise Imaging Platform, version Visage 7.1.18h (or higher). Visage Ease VP is available for download via the Apple App Store.

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