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UNC-Chapel Hill and Emory University Lead Initiative to Build World's Largest Rare Disease Data Resource

UNC-Chapel Hill and Emory University Lead Initiative to Build World's Largest Rare Disease Data Resource

UNC-Chapel Hill and Emory University are spearheading a groundbreaking research initiative to establish the world's largest comprehensive data resource for diagnosing rare diseases. This project, supported by an award of up to $35 million from the Advanced Research Projects Agency for Health (a U.S. Department of Health and Human Services agency), aims to leverage artificial intelligence (AI) to drive insights, facilitate earlier diagnoses, improve medical care, and accelerate treatment discovery. The initiative will acquire data from various sources, including patient registries, real-world clinical data, health records, insurance claims, medical imaging, video technologies, and patient surveys. The goal is to create a large-scale dataset spanning approximately 2,700 rare diseases to train AI models. These models will then be deployed in diagnostic settings to help clinicians interpret findings more effectively and provide answers to patients sooner. Melissa Haendel, lead scientist on the project, emphasi...

McKesson's Ontada Genospace Team Seeks Data Scientist to Advance Precision Medicine with AI

McKesson's Ontada Genospace Team Seeks Data Scientist to Advance Precision Medicine with AI

McKesson's Ontada Genospace team is actively seeking a Data Scientist to join their efforts in transforming precision medicine. This role focuses on leveraging advanced analytics, machine learning, and AI-driven insights to convert complex healthcare, genomic, and clinical data into actionable intelligence. The Data Scientist will be responsible for developing predictive models, building analytical solutions, and providing data-driven recommendations. This involves applying machine learning, statistical modeling, and generative AI techniques. The position requires close collaboration with product managers, engineers, clinicians, and scientists to further precision medicine solutions utilized by leading healthcare organizations. Key responsibilities include analyzing and validating healthcare data, deploying machine learning models, developing AI and large language model (LLM) solutions using prompt engineering, performing statistical analyses, and creating data visualizations. Candidates should possess a M...

Parents Utilize AI and Genome Sequencing to Diagnose Daughter's Rare Illness

Parents Utilize AI and Genome Sequencing to Diagnose Daughter's Rare Illness

In 2023, Hilary and Matt Eaton, both scientists in the biotech industry, spent approximately $4,500 to sequence the entire genomes of their family members to understand their daughter Olivia's persistent health issues. Olivia, at age five, suffered from frequent illnesses and developmental delays that doctors struggled to fully explain, despite a diagnosis of a connective tissue disorder. The Eatons used ChatGPT to analyze Olivia's genome sequencing data and lab results, identifying potential genetic mutations and possible diagnoses. While the AI initially flagged a deadly mutation that later proved to be an error in the sequencing data, it ultimately helped them identify CVID (common variable immunodeficiency) as a possible cause for her low antibody count. Further AI-assisted research led them to discover Olivia had Okur-Chung neurodevelopmental syndrome, a rare genetic disorder affecting approximately 1 in 100,000 people. This diagnosis provided a clearer understanding of her symptoms and led to effecti...

Parents Utilize AI Chatbot to Aid in Diagnosing Daughter's Rare Medical Conditions

Parents Utilize AI Chatbot to Aid in Diagnosing Daughter's Rare Medical Conditions

Hilary and Matt Eaton, both scientists in the biotech industry, used ChatGPT to help understand their daughter Olivia's complex and confounding medical symptoms. For most of her 5-year-old life, Olivia experienced frequent illnesses, developmental delays, and slow wound healing. After receiving alarming lab results showing low antibody levels, Hilary Eaton input Olivia's symptoms and test results into ChatGPT. The chatbot suggested common variable immunodeficiency (CVID) as a possible diagnosis, which, while not the ultimate cause, provided a starting point for further medical discussions. The Eatons also used AI to analyze their family's genome sequencing data, identifying potential genetic mutations. This AI-assisted research helped them uncover that Olivia had Okur-Chung neurodevelopmental syndrome, a rare genetic disorder affecting approximately 1 in 100,000 people, which explained her low antibody production and other symptoms. Their use of AI also led them to suggest an EEG for Olivia's motor tics, w...

USC Researchers Develop Blood-Based Algorithm to Enhance Alzheimer's Trial Screening

USC Researchers Develop Blood-Based Algorithm to Enhance Alzheimer's Trial Screening

Researchers at the Keck School of Medicine of the University of Southern California (USC) have developed a blood-plasma screening algorithm designed to improve the efficiency of recruiting participants for Alzheimer's prevention trials. This new tool aims to identify individuals more likely to meet the amyloid thresholds required for trial enrollment, thereby reducing the need for costly and time-consuming positron emission tomography (PET) scans. The algorithm integrates two plasma biomarkers: the amyloid-beta ratio, which indicates early brain amyloid, and phosphorylated tau 217 (p-tau217), a direct marker of amyloid burden. Additionally, age and apolipoprotein E4 (APOE4) carrier status are factored in to refine individual risk estimates. The development of this algorithm utilized data from 1,080 participants in the AHEAD 3-45 phase 3 trial and was validated using an independent cohort from the Wisconsin Registry for Alzheimer’s Prevention. The algorithm was iteratively refined during the AHEAD trial's r...

AI Transforms Musculoskeletal Surgery with Enhanced Diagnosis, Planning, and Post-Operative Monitoring

AI Transforms Musculoskeletal Surgery with Enhanced Diagnosis, Planning, and Post-Operative Monitoring

Artificial intelligence (AI) is increasingly being integrated into musculoskeletal (MSK) surgery, moving from research into clinical practice. AI applications span diagnostic imaging, pre-operative planning, robotic-assisted procedures, and post-operative monitoring. In diagnostics, deep learning systems analyze radiographs, CT scans, and MRIs for fracture detection, osteoarthritis grading, and tumor recognition, acting as an 'intelligent second reader' to prioritize urgent cases and reduce missed diagnoses. For surgical planning, AI-assisted segmentation and predictive modeling help in implant selection and simulating operative strategies, aiming for more standardized and individualized approaches. In the operating room, AI-assisted navigation systems support precise component positioning during arthroplasty and pedicle screw placement in spinal surgery. Post-operatively, wearable sensors and smartphone applications continuously assess mobility, gait, and adherence to rehabilitation programs, allowing for...

Root Insurance Seeks Staff Data Scientist to Advance AI-Driven Marketing Strategies

Root Insurance Seeks Staff Data Scientist to Advance AI-Driven Marketing Strategies

Root Insurance Seeks Staff Data Scientist to Advance AI-Driven Marketing Strategies

TRG Screen, a Vista Equity Partners Portfolio Company, Seeks Graduate Market Data Analyst

TRG Screen, a Vista Equity Partners Portfolio Company, Seeks Graduate Market Data Analyst

TRG Screen, a Vista Equity Partners Portfolio Company, Seeks Graduate Market Data Analyst

BrainChip Reports Strong Commercial Pipeline and Akida 1500 Chip Sales Amidst Execution Concerns

BrainChip Reports Strong Commercial Pipeline and Akida 1500 Chip Sales Amidst Execution Concerns

BrainChip Reports Strong Commercial Pipeline and Akida 1500 Chip Sales Amidst Execution Concerns

AI Chatbots Show Varied Performance in Breast Cancer Information, Study Finds

AI Chatbots Show Varied Performance in Breast Cancer Information, Study Finds

A recent study published in *Scientific Reports* conducted a head-to-head comparison of five leading large language models (LLMs)—ChatGPT-5.2, ChatGPT-4o, Gemini 3.0, DeepSeek, and ERNIE Bot—to evaluate their effectiveness in providing breast cancer health information. The research assessed the chatbots using 90 multiple-choice questions, 10 de-identified clinical cases, and responses to 20 common patient concerns. While all five models demonstrated high accuracy on standardized breast cancer knowledge questions, ranging from 82.22% to 94.44%, their performance varied significantly in linguistic complexity and expert-rated quality measures. Human experts rated ChatGPT-5.2 and DeepSeek highest for completeness, while Gemini 3.0 received the highest readability score. DeepSeek also produced the lowest reading-difficulty score in the automated Chinese-language assessment. The study concluded that no single model excelled across all measures, suggesting the need for multi-faceted evaluation of LLMs in healthca...

Tempus Secures $9.5 Million ARPA-H Funding for Autonomous AI in Cardiology

Tempus Secures $9.5 Million ARPA-H Funding for Autonomous AI in Cardiology

Tempus AI, Inc. has been awarded up to $9.5 million in funding from the Advanced Research Projects Agency for Health (ARPA-H), an agency within the U.S. Department of Health and Human Services. This funding, provided through ARPA-H’s ADVOCATE (Agentic AI-EnableD CardioVascular CAre TransfOrmation) program, is designated for the development of the first autonomous clinical AI agent in cardiology. This AI agent is designed to provide safe and effective care to patients suffering from heart failure without direct human intervention. The initiative aims to create a highly scalable AI agent that acts as an extension of the clinician team, offering reliable, 24-hour care. The solution will involve continuous surveillance of both clinical data from electronic health records and consumer-generated data from home-based heart rate monitors. This platform will feature a patient-facing autonomous agent capable of managing symptoms, medications, virtual rehabilitation, and scheduling, while also integrating with electr...

Helix Launches Whole Exome+® Sequencing to Accelerate Rare Disease Diagnosis

Helix Launches Whole Exome+® Sequencing to Accelerate Rare Disease Diagnosis

Helix, a leading enterprise genomics platform, has announced the nationwide availability of its Whole Exome+® Sequencing (WES+) diagnostic test. This new offering aims to provide a more comprehensive genetic evaluation for patients with rare and unexplained genetic conditions, integrating broad exome coverage, mitochondrial genome analysis, and genome-wide digital karyotype into a single order. The WES+ test is designed to reduce the time to diagnosis for patients who have often undergone years of inconclusive testing. According to Dr. Cassie Hajek, Medical Director at Helix, WES+ offers clinicians a comprehensive genomic picture from the initial visit, providing broad visibility into potential genomic factors. The launch aligns with evolving clinical guidelines from organizations like the American College of Medical Genetics and the American Academy of Pediatrics, which increasingly recommend exome or genome sequencing as a priority diagnostic approach for conditions such as unexplained developmental dela...