AIMC Topic: Precision Medicine

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An AI-assisted morphoproteomic approach is a supportive tool in esophagitis-related precision medicine.

EMBO molecular medicine
Esophagitis is a frequent, but at the molecular level poorly characterized condition with diverse underlying etiologies and treatments. Correct diagnosis can be challenging due to partially overlapping histological features. By proteomic profiling of...

Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence.

Nature cancer
Despite advances in precision oncology, clinical decision-making still relies on limited variables and expert knowledge. To address this limitation, we combined multimodal real-world data and explainable artificial intelligence (xAI) to introduce AI-...

ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction.

PLoS computational biology
Personalized cancer drug treatment is emerging as a frontier issue in modern medical research. Considering the genomic differences among cancer patients, determining the most effective drug treatment plan is a complex and crucial task. In response to...

ExPDrug: Integration of an interpretable neural network and knowledge graph for pathway-based drug repurposing.

Computers in biology and medicine
Precision medicine aims to provide personalized therapies by analyzing patient molecular profiles, often focusing on gene expression data. However, effectively linking these data to actionable drug discovery for clinical application remains challengi...

Intricacies of human-AI interaction in dynamic decision-making for precision oncology.

Nature communications
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics...

The clinical application of artificial intelligence in cancer precision treatment.

Journal of translational medicine
BACKGROUND: Artificial intelligence has made significant contributions to oncology through the availability of high-dimensional datasets and advances in computing and deep learning. Cancer precision medicine aims to optimize therapeutic outcomes and ...

Exploiting the similarity of dissimilarities for biomedical applications and enhanced machine learning.

PLoS computational biology
The "similarity of dissimilarities" is an emerging paradigm in biomedical science with significant implications for protein function prediction, machine learning (ML), and personalized medicine. In protein function prediction, recognizing dissimilari...

Multicategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study.

Statistical methods in medical research
One primary goal of precision medicine is to estimate the individualized treatment rules that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in practice. However, most...

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Advances in nutrition (Bethesda, Md.)
Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and other medical complications. Advances in technology that enable continuous biological data collection...

An in-depth review of AI-powered advancements in cancer drug discovery.

Biochimica et biophysica acta. Molecular basis of disease
The convergence of artificial intelligence (AI) and genomics is redefining cancer drug discovery by facilitating the development of personalized and effective therapies. This review examines the transformative role of AI technologies, including deep ...