AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.

PloS one
Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for preventing progression and formulating effective treatment plans. This study aims to develop a novel deep learning (DL) model, Hybrid-RViT, to enhanc...

4D trajectory prediction and conflict detection in terminal areas based on an improved convolutional network.

PloS one
At present, the passenger traffic volume of civil aviation is gradually increasing, and the scale of the airline network is gradually expanding. In order to optimize the air traffic service mode more safely and scientifically, the International Civil...

SugarViT-Multi-objective regression of UAV images with Vision Transformers and Deep Label Distribution Learning demonstrated on disease severity prediction in sugar beet.

PloS one
Remote sensing and artificial intelligence are pivotal technologies of precision agriculture nowadays. The efficient retrieval of large-scale field imagery combined with machine learning techniques shows success in various tasks like phenotyping, wee...

Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT.

PloS one
PURPOSE: This study aims to explore the potential of non-contrast abdominal CT radiomics and deep learning models in accurately diagnosing fatty liver.

Table tennis coaching system based on a multimodal large language model with a table tennis knowledge base.

PloS one
UNLABELLED: Table tennis is one of the most popular sports in the world, and it plays a positive role in the overall development of people's physical and mental health. This study develops an AI table tennis coaching system using a Multimodal Large L...

Deep learning based screening model for hip diseases on plain radiographs.

PloS one
INTRODUCTION: The interpretation of plain hip radiographs can vary widely among physicians. This study aimed to develop and validate a deep learning-based screening model for distinguishing normal hips from severe hip diseases on plain radiographs.

The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...

Predicting software reuse using machine learning techniques-A case study on open-source Java software systems.

PloS one
Software reuse is an essential practice to increase efficiency and reduce costs in software production. Software reuse practices range from reusing artifacts, libraries, components, packages, and APIs. Identifying suitable software for reuse requires...

Image captioning in Bengali language using visual attention.

PloS one
Automatically generating image captions poses one of the most challenging applications within artificial intelligence due to its integration of computer vision and natural language processing algorithms. This task becomes notably more formidable when...

ILR-Net: Low-light image enhancement network based on the combination of iterative learning mechanism and Retinex theory.

PloS one
Images captured in nighttime or low-light environments are often affected by external factors such as noise and lighting. Aiming at the existing image enhancement algorithms tend to overly focus on increasing brightness, while neglecting the enhancem...