Latest AI and machine learning research in us health policy for healthcare professionals.
Autoregressive sequence modeling stands as the cornerstone of modern Generative AI, powering results across diverse modalities ranging from text generation to image generation. However, a fundamental limitation of this paradigm is the rigid structural coupling of model capacity to computational cost: expanding a model's parametric memory -- its repository of factual knowledge or visual patterns --...
Pain management in intensive care usually involves complex trade-offs between therapeutic goals and patient safety, since both inadequate and excessive treatment may induce serious sequelae. Reinforcement learning can help address this challenge by learning medication dosing policies from retrospective data. However, prior work on sedation and analgesia has optimized for objectives that do not val...
The ventral tegmental area is the primary source of dopaminergic input to the human prefrontal cortex and plays a central role in reinforcement learni...
Importance: Emerging evidence suggests healthcare AI systems may exhibit deceptive alignment (appearing safe during validation while optimizing for mi...
Allogeneic hematopoietic cell transplantation (allo-HCT) is potentially curative for older adults with hematologic malignancies. Concerns on nonrelaps...
Recently, research into chatbots (also known as conversational agents, AI agents, voice assistants), which are computer applications using artificia...
In the past, the chest X-ray (CXR) was a traditional age and amount requirement used to assess potential mortality risk in life insurance applicants. ...
is a leading cause of foodborne illnesses globally, with significant mortality rates, especially among vulnerable populations. Traditional serotyping...
Plastic surgery, by nature an innovative discipline, has historically relied on clinical case reports to advance its techniques. Often unique, these c...
The diagnostic value of electrocardiogram (ECG) lies in its dynamic characteristics, ranging from rhythm fluctuations to subtle waveform deformation...
Navigating everyday social situations often requires juggling conflicting goals, such as conveying a harsh truth, maintaining trust, all while still...
The application scope of Large Language Models (LLMs) continues to expand, leading to increasing interest in personalized LLMs that align with human...
Individuals often navigate several options with incomplete knowledge of their own preferences. Information provisioning tools such as public ranking...
The integration of chatbots into psychiatry introduces a novel approach to support clinical decision-making, but biases in their recommendations pose ...
BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-mak...
The swift evolution of telehealth has revolutionized how medical professionals deliver healthcare services and boost convenience and accessibility. ...
The COVID-19 pandemic response relied heavily on statistical and machine learning models to predict key outcomes such as case prevalence and fatalit...
Rapid integration of large language models (LLMs) into societal applications has intensified concerns about their alignment with universal ethical p...
Abortion is a critical health issue that leads to numerous complications, maternal deaths, and significant financial burdens on women, families, and h...
The left atrium (LA) plays a pivotal role in modulating left ventricular filling, but our comprehension of its hemodynamics is significantly limited...