AIMC Topic: Precision Medicine

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Artificial intelligence-based personalized clinical decision-making for patients with localized prostate cancer: surgery versus radiotherapy.

The oncologist
BACKGROUND: Surgery and radiotherapy are primary nonconservative treatments for prostate cancer (PCa). However, personalizing treatment options between these treatment modalities is challenging due to unclear criteria. We developed an artificial inte...

ANALYSIS OF CHALLENGES AND POSSIBILITIES OF USING ARTIFICIAL INTELLIGENCE IN MEDICAL DIAGNOSTICS.

Georgian medical news
BACKGROUND: This study aims to analyze the geographical distribution of different AI types and applications, document implementation challenges, and assess outcomes of interest as well as potential opportunities for increasing healthcare efficiency.

Survival causal rule ensemble method considering the main effect for estimating heterogeneous treatment effects.

Statistics in medicine
With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship between treatment effects and patient characteristics. The treatment effects for patients with differ...

Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL).

Frontiers in bioscience (Landmark edition)
In this comprehensive review, we delve into the transformative role of artificial intelligence (AI) in refining the application of multi-omics and spatial multi-omics within the realm of diffuse large B-cell lymphoma (DLBCL) research. We scrutinized ...

DeepDR: a deep learning library for drug response prediction.

Bioinformatics (Oxford, England)
SUMMARY: Accurate drug response prediction is critical to advancing precision medicine and drug discovery. Recent advances in deep learning (DL) have shown promise in predicting drug response; however, the lack of convenient tools to support such mod...

Multimodal deep learning approaches for precision oncology: a comprehensive review.

Briefings in bioinformatics
The burgeoning accumulation of large-scale biomedical data in oncology, alongside significant strides in deep learning (DL) technologies, has established multimodal DL (MDL) as a cornerstone of precision oncology. This review provides an overview of ...

TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision mana...

Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era.

World journal of gastroenterology
Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer with a poor prognosis. Early diagnosis and prognosis assessment are crucial for improving the survival rate of ESCC patients. With the advancement of ...

A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology.

Briefings in functional genomics
Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biological interaction between different omics. Machine learning approaches have been extensively employed in this context over the years. This review aims t...

Model ensembling as a tool to form interpretable multi-omic predictors of cancer pharmacosensitivity.

Briefings in bioinformatics
Stratification of patients diagnosed with cancer has become a major goal in personalized oncology. One important aspect is the accurate prediction of the response to various drugs. It is expected that the molecular characteristics of the cancer cells...