Although recent large language models (LLMs) have demonstrated impressive capabilities in few-shot or zero-shot learning, their effectiveness in clinical diagnosis remains unproven. Here we present MedFound, a generalist medical language model with 176 billion parameters, pre-trained on a large-scale...
The AI system, deployed on cloud servers, enables real-time analysis via a smartphone application, with the LLM providing contextual medical advice based on CNN outputs. The system achieved a diagnostic accuracy of 97.6%, comparable to otolaryngology specialists (98.2%) and significantly higher than...
agriculture Article Tomato Leaf Disease Diagnosis Based on Improved Convolution Neural Network by Attention Module Shengyi Zhao, Yun Peng, Jizhan Liu * and Shuo Wu Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China; ...
First we'll discuss what an LLM is and some of the strengths and weaknesses of these models, looking at a handful of models and approaches
inferential diagnosis with a self-bootstrapping strategy-based chain-of-thought approach and introduced a unified preference alignment framework to align it with standard clinical practice. Extensive experiments demonstrate that our medical LLM outperforms other baseline LLMs and specialized models in in-...
N-terminal pro hormone B-type natriuretic peptide (NT-proBNP) is commonly elevated in KD patients [7] and is useful in diagnosis with a pooled sensitivity of 80–89% and positive likelihood ratio of 3.2 [18], [19]. NT-proBNP may also potentially serve as a prognostic marker for IVIG ...
4.2. Early warning systems that rely on syndromic surveillance Individuals typically seek medical attention after symptoms have manifested for some time, resulting in a delay between symptom onset and diagnosis. As a result, symptom-based early warning systems can often detect anomalies earlier than ca...
(4) the broad tasks that LLMs have been used for in clinical medicine and what performance have LLMs achieved on these tasks. Objective 2: Determine the extent that LLMs can be used to summarise or extract information from MIMIC-III data. The student ...
The Promise and Pitfalls of AI in the Complex World of Diagnosis, Treatment, and Disease Management This conversation is part of a series of interviews in whichJAMAEditor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, and expert guests explore issues surrounding the rapidly evolving inte...
Disease progression can differ between different patients with the same diagnosis or within a patient at different time points. Indeed, health and disease can be seen as variable entities on continuous scales. Such variations depend on genetic or environmental factors, such as pollution, lifestyle, ...