Artificial intelligence-powered generative language models (GLMs), such as ChatGPT, Perplexity AI, and Google Bard, have the potential to provide personalized learning, unlimited practice opportunities, interactive engagement 24/7, with immediate feedback. However, fully utilize GLMs, properly formulated instructions are essential. Prompt engineering is a systematic approach effectively communicating GLMs achieve desired results. Well-crafted prompts yield good responses from GLM, while...

Background Generative artificial intelligence (AI) models, exemplified by systems such as ChatGPT, Bard, and Anthropic, are currently under intense investigation for their potential to address existing gaps in mental health support. One implementation of these large language models involves the development health-focused conversational agents, which utilize pre-structured prompts facilitate user interaction without requiring specialized knowledge prompt engineering. However, uncertainties...

The rapid advancements in artificial intelligence, particularly generative AI and large language models, have unlocked new possibilities for revolutionizing healthcare delivery. However, harnessing the full potential of these technologies requires effective prompt engineering—designing optimizing input prompts to guide systems toward generating clinically relevant accurate outputs. Despite importance engineering, medical education has yet fully incorporate comprehensive training on this...

Background ChatGPT-4 is a large language model with promising healthcare applications. However, its ability to analyze complex clinical data and provide consistent results poorly known. Compared validated tools, this study evaluated ChatGPT-4’s risk stratification of simulated patients acute nontraumatic chest pain. Methods Three datasets case studies were created: one based on the TIMI score variables, another HEART third comprising 44 randomized variables related non-traumatic pain...

VOICE Credit: This activity has been approved for 1.0 (Category A) credit. For CE credit, participants can access this on page 17A or the SNM Web site (http://www.snm.org/ce_online) through December 31, 2012. You must answer 80% of questions correctly to receive CEH (Continuing Education Hour)

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Introduction: Large language models (LLMs) are increasingly used in clinical medicine to provide emotional support, deliver cognitive-behavioral therapy, and assist triage diagnosis. However, as LLMs integrated into mental health applications, assessing their inherent personality traits evaluating divergence from expected neutrality is essential. This study characterizes the profiles exhibited by using two validated frameworks: Open Extended Jungian Type Scales (OEJTS) Big Five Personality...

This article proposes the Percent Fragility Index (PFI) as an improved measure of statistical fragility in biomedical research. The PFI quantifies percentage change outcomes needed to a study's significance from positive negative or vice-versa. improves upon existing indices by providing intuitive statistic that is easy grasp and accommodating both dichotomous continuous variables. approach minimizes dependency on sample size, limitation commonly used (FI) Quotient (FQ). FI measures minimum...

ABSTRACT The safety of large language models (LLMs) as mental health chatbots is not fully established. This study evaluated the risk escalation responses publicly available ChatGPT conversational agents when presented with prompts increasing depression severity and suicidality. average referral point to a human was at midpoint escalating prompts. However, most only definitively recommended professional help highest level risk. Few included crisis resources like suicide hotlines. results...

Homelessness persists as a critical global issue despite myriad interventions. This study analyzed state-level differences in homelessness rates across the United States to identify influential societal factors help guide resource prioritization.

Background In biostatistics, assessing the fragility of research findings is crucial for understanding their clinical significance. This study focuses on index, unit and relative risk index as measures to evaluate statistical fragility. The indices assess susceptibility p-values change significance with minor alterations in outcomes within a 2x2 contingency table. contrast, quantifies deviation observed from therapeutic equivalence, point at which equals 1. While have intuitive appeal been...

Statistical significance is widely used to evaluate research findings but has limitations around reproducibility. Measures of statistical fragility aim quantify robustness against violations assumptions. However, dependence on sample size and single unit changes restricts indices like the index quotient. The Robustness Index (RI) proposed overcome these independently study's size. RI measures how altering affects significance. For insignificant findings, multiplied until reached;...

Our website uses cookies to enhance your experience. By continuing use our site, or clicking "Continue," you are agreeing Cookie Policy | Continue JAMA HomeNew OnlineCurrent IssueFor Authors Publications Network Open Cardiology Dermatology Health Forum Internal Medicine Neurology Oncology Ophthalmology Otolaryngology–Head & Neck Surgery Pediatrics Psychiatry Archives of (1919-1959) Podcasts Clinical Reviews Editors' Summary Medical News Author Interviews More JN Learning /...

Background: Climate change represents a critical global challenge, hindered by skepticism towards data manipulation and politicization. Trust in climate its policies is essential for effective action. Objective: This perspective paper explores the synergistic potential of blockchain technology artificial intelligence (AI) addressing how their integration can enhance transparency, reliability, accessibility science. Methods: The analyzes roles enhancing traceability, efficiency carbon credit...

<ns4:p>Healthcare providers experience moral injury when their internal ethics are violated. The routine and direct exposure to ethical violations makes clinicians vulnerable harm. fundamental in health care typically fall into the four broad categories of patient autonomy, beneficence, nonmaleficence, social justice. Patients have a right determine own goals medical care, that is, they autonomy. When this principle is violated, occurs. Beneficence desire help people, so delivery proper...