AI Medical Compendium Topic

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Neoplasms

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Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.

International journal of molecular sciences
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...

Equitable machine learning counteracts ancestral bias in precision medicine.

Nature communications
Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease. Therapeutics and outcomes remain hidden because we lack insights that could be gained from analyzing...

Interpretable Multimodal Fusion Model for Bridged Histology and Genomics Survival Prediction in Pan-Cancer.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Understanding the prognosis of cancer patients is crucial for enabling precise diagnosis and treatment by clinical practitioners. Multimodal fusion models based on artificial intelligence (AI) offer a comprehensive depiction of the tumor heterogeneit...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

Scientific reports
To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, aiming to enhance their quality of life. A non-randomized controlled trial was conducted from September 2022 to March 2024, involving 144 chemotherapy ...

A deep-learning model for quantifying circulating tumour DNA from the density distribution of DNA-fragment lengths.

Nature biomedical engineering
The quantification of circulating tumour DNA (ctDNA) in blood enables non-invasive surveillance of cancer progression. Here we show that a deep-learning model can accurately quantify ctDNA from the density distribution of cell-free DNA-fragment lengt...

Hallmarks of artificial intelligence contributions to precision oncology.

Nature cancer
The integration of artificial intelligence (AI) into oncology promises to revolutionize cancer care. In this Review, we discuss ten AI hallmarks in precision oncology, organized into three groups: (1) cancer prevention and diagnosis, encompassing can...

A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection.

Computers in biology and medicine
Cancer is a severe threat to public health. Early diagnosis of disease is critical, but the lack of experts in this field, the personal assessment process, the clinical workload, and the high level of similarity in disease classes make it difficult. ...

Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.

IEEE journal of biomedical and health informatics
A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repurposing, and resistance reversal. While targeted anticancer therapies have shown promise, not all cancers have well-established biomarkers to stratify...

TARSL: Triple-Attention Cross-Network Representation Learning to Predict Synthetic Lethality for Anti-Cancer Drug Discovery.

IEEE journal of biomedical and health informatics
Cancer is a multifaceted disease that results from co-mutations of multi biological molecules. A promising strategy for cancer therapy involves in exploiting the phenomenon of Synthetic Lethality (SL) by targeting the SL partner of cancer gene. Since...

StackTHP: A stacking ensemble model for accurate prediction of tumor-homing peptides in cancer therapy.

Computers in biology and medicine
The tumor-homing peptides (THPs) have emerged as one of the attractive resources for targeted cancer therapy, being able to bind and penetrate tumor cells selectively while ignoring adjacent healthy tissues. Therefore, the computational models to pre...