AIMC Topic: Humans

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Assessing the Responses of Large Language Models (ChatGPT-4, Claude 3, Gemini, and Microsoft Copilot) to Frequently Asked Questions in Retinopathy of Prematurity: A Study on Readability and Appropriateness.

Journal of pediatric ophthalmology and strabismus
PURPOSE: To assess the appropriateness and readability of responses provided by four large language models (LLMs) (ChatGPT-4, Claude 3, Gemini, and Microsoft Copilot) to parents' queries pertaining to retinopathy of prematurity (ROP).

Large language models to facilitate pregnancy prediction after in vitro fertilization.

Acta obstetricia et gynecologica Scandinavica
We evaluated the efficacy of large language models (LLMs), specifically, generative pre-trained transformer-4 (GPT-4), in predicting pregnancy following in vitro fertilization (IVF) treatment and compared its accuracy with results from an original pu...

Effects of interval treadmill training on spatiotemporal parameters in children with cerebral palsy: A machine learning approach.

Journal of biomechanics
Quantifying individualized rehabilitation responses and optimizing therapy for each person is challenging. For interventions like treadmill training, there are multiple parameters, such as speed or incline, that can be adjusted throughout sessions. T...

CK-ATTnet: Medical image segmentation network based on convolutional kernel attention.

Computers in biology and medicine
The medical image partition model has a wide range of application prospects in medical diagnosis and treatment and has become an important auxiliary method to improve the diagnostic level by medical imaging analysis. After the feature extraction abil...

Predicting ergonomic risk among laboratory technicians using a Cheetah Optimizer-Integrated Deep Convolutional Neural Network.

Computers in biology and medicine
Medical laboratory technicians play a significant role in clinical units by conducting diagnostic tests and analyses. However, their job nature involving repetitive motions, prolonged standing or sitting, etc., leads to potential ergonomic risks. Thi...

LTMSegnet: Lightweight multi-scale medical image segmentation combining Transformer and MLP.

Computers in biology and medicine
Medical image segmentation is currently of a priori guiding significance in medical research and clinical diagnosis. In recent years, neural network-based methods have improved in terms of segmentation accuracy and become the mainstream in the field ...

Plasma protein-based identification of neuroimage-driven subtypes in mild cognitive impairment via protein-protein interaction aware explainable graph propagational network.

Computers in biology and medicine
As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment according to its subtypes for the effective prevention and management of dementia progression. Based on the neuropathological characteristics, MCI can b...

Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.

Bioorganic chemistry
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literatu...

WISE: Efficient WSI selection for active learning in histopathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Deep neural network (DNN) models have been applied to a wide variety of medical image analysis tasks, often with the successful performance outcomes that match those of medical doctors. However, given that even minor errors in a model can impact pati...