Tag: medical AI
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Brainomix Earns Top Honor in Global Health Tech Competition for 360 Stroke AI
Global Recognition for Brainomix 360 Stroke AI Brainomix, a leader in AI-powered medical imaging, has been awarded top honors in the prestigious Global Health Tech Competition. The company earned first place in the Science category for its Brainomix 360 Stroke technology, a comprehensive system that combines advanced AI with imaging to assist clinicians in the…
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NCH Adopts Groundbreaking AI to Detect Hidden Heart Attack Risk a Decade Early in Preventive Cardiology
Breaking Ground in Preventive Cardiology In a landmark move for American healthcare, Naples Community Hospital (NCH) has become the first U.S. hospital to deploy artificial intelligence that detects hidden heart attack risk up to a decade in advance. The collaboration with Caristo Diagnostics positions NCH at the forefront of preventive cardiology, offering physicians a powerful…
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AI Improves Detection, Reduces ‘False Positives’ on Mammograms
AI Improves Detection and Reduces False Positives in Mammography Artificial intelligence is making meaningful strides in breast cancer screening. By enhancing the accuracy of mammograms, AI helps radiologists detect cancers earlier while reducing the number of false positives that lead to unnecessary follow-up procedures. One health system at the forefront of this shift is California-based…
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Explainable AI in Cancer Detection: Dr. Sakib Mostafa’s Path from Fear to Innovation
Unpacking the Black Box: Why Explainable AI Matters Artificial intelligence is reshaping healthcare, but its most consequential risks aren’t tubes of metal marching toward dystopian futures. They’re systems whose decisions are opaque, creating trust gaps when lives are on the line. Dr. Sakib Mostafa’s work centers on explainable AI—the science of making AI decisions understandable…
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Unpacking the black box of AI: Explainable AI in cancer detection with Dr. Sakib Mostafa
Understanding the black box: why explainable AI matters Artificial intelligence has advanced rapidly, but one of its most consequential challenges remains the so-called “black box” problem. Dr. Sakib Mostafa, a Bangladeshi-Canadian researcher, frames this not as a sci‑fi nightmare but as a practical hurdle: the results that AI models produce can be correct yet inexplicable.…
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Unpacking the AI Black Box: Explainable AI in Cancer Detection
Introduction: The fear that fuels curiosity Dr. Sakib Mostafa’s journey into artificial intelligence is shaped by a mix of fascination and apprehension. As a child in Bangladesh, he was captivated by how machines might transform the world, yet unsettled by the dangers imagined in films and science fiction. His approach to risk has always been…
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Large Language Models in Lung Cancer: A Comprehensive Systematic Review
Introduction: The Rise of LLMs in Lung Cancer Care Large language models (LLMs) are increasingly explored as tools to assist in the full cycle of lung cancer (LC) management, from prevention and screening to diagnosis, treatment planning, and supportive care. This systematic review synthesizes recent evidence on how LLMs are being applied to LC, what…
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A human-LLM collaborative annotation approach for screening articles on precision oncology randomized controlled trials
Why a human-LLM collaborative approach matters Systematic reviews in precision oncology require screening thousands of articles to identify randomized controlled trials (RCTs) that illuminate biomarker-driven therapies and targeted interventions. Manual screening, while thorough, is time-consuming and resource-intensive. Large language models (LLMs) can accelerate triage by quickly categorizing relevance and extracting key trial details, but their…