Artificial Intelligence Medical Compendium

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

Showing 60,691 to 60,700 of 228,072 articles

Alzheimer's disease prediction via an explainable CNN using genetic algorithm and SHAP values.

PloS one
Convolutional neural networks (CNNs) are widely recognized for their high precision in image classification. Nevertheless, the lack of transparency in these black-box models raises concerns in sensitive domains such as healthcare, where understanding... read more 

Radiomics profiling combined with clinical risk factors for preoperative Lymphatic Metastasis prediction in Colorectal cancer: A multicenter study.

PloS one
PURPOSE: Accurate preoperative assessment of regional lymphatic metastases (LNM) is essential for effective surgical selection of patients with colorectal cancer (CRC). This study aimed to develop a machine learning (ML) model that integrates radiomi... read more 

Data Science Education for Residents, Researchers, and Students in Psychiatry and Psychology: Program Development and Evaluation Study.

JMIR medical education
BACKGROUND: The use of artificial intelligence (AI) to analyze health care data has become common in behavioral health sciences. However, the lack of training opportunities for mental health professionals limits clinicians' ability to adopt AI in cli... read more 

A Mixed Dual-Branch Network for Detecting Cervical Spondylotic Myelopathy and Parkinsonian Syndromes via Gait Analysis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cervical spondylotic myelopathy (CSM) and parkinsonian syndromes (PS) present similar motor symptoms, often causing misdiagnosis due to current clinical diagnostic limitations. Misdiagnosis can exacerbate patient conditions or result in unnecessary s... read more 

Confidence-Based Batch Ordering in Continual Learning: A Curriculum Learning Approach for Single-Cell RNA Sequencing Data.

IEEE transactions on computational biology and bioinformatics
Training machine learning models on large datasets, such as those derived from single-cell RNA sequencing (scRNA-seq), poses significant challenges due to high computational and memory demands. Additionally, integrating data from diverse sources intr... read more 

Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models.

IEEE transactions on medical imaging
Incoherent k-space undersampling and deep learning-based reconstruction methods have shown great success in accelerating MRI. However, the performance of most previous methods will degrade dramatically under high acceleration factors, e.g., 8× or hig... read more 

Learning-Based Multi-View Stereo: A Survey.

IEEE transactions on pattern analysis and machine intelligence
3D reconstruction aims to recover the dense 3D structure of a scene. It plays an essential role in various applications such as Augmented/Virtual Reality (AR/VR), autonomous driving and robotics. Leveraging multiple views of a scene captured from dif... read more 

Order-Aware Deep Learning for Drug Combination Benefit Prediction in Cancer Cell Lines.

IEEE journal of biomedical and health informatics
Drug combination therapy has exhibited favorable effects in treating cancer patients, with less toxicity and adverse reactions compared to monotherapy. To accelerate the discovery of therapeutic drug combinations, numerous computational methods have ... read more 

Opportunities and Challenges in Precision Neurotherapeutics.

Annual review of biomedical engineering
Precision neurotherapeutics represents a transformative paradigm shift from standardized "one-size-fits-all" treatments of neurological, neurodegenerative, and/or psychiatric disorders toward individualized interventions that leverage patient-specifi... read more 

Unified Graph-Based Interatomic Potential for Perovskite Structure Optimization.

Journal of chemical information and modeling
Halide perovskites (HaPs) hold immense potential for applications such as optoelectronics and catalysis. Their vast compositional space, spanning bulk alloys, defects, impurities, surfaces, and surface defects, poses significant challenges for effici... read more