AIMC Topic: Precision Medicine

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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...

Advanced NLP-driven predictive modeling for tailored treatment strategies in gastrointestinal cancer.

SLAS technology
Gastrointestinal cancer represents a significant health burden, necessitating innovative approaches for personalized treatment. This study aims to develop an advanced natural language processing (NLP)-driven predictive modeling framework for tailored...

DRExplainer: Quantifiable interpretability in drug response prediction with directed graph convolutional network.

Artificial intelligence in medicine
Predicting the response of a cancer cell line to a therapeutic drug is pivotal for personalized medicine. Despite numerous deep learning methods that have been developed for drug response prediction, integrating diverse information about biological e...

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine.

Epilepsy & behavior : E&B
Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EE...

Advances of artificial intelligence in clinical application and scientific research of neuro-oncology: Current knowledge and future perspectives.

Critical reviews in oncology/hematology
Brain tumors refer to the abnormal growths that occur within the brain's tissue, comprising both primary neoplasms and metastatic lesions. Timely detection, precise staging, suitable treatment, and standardized management are of significant clinical ...

Enhancing Personalized Chemotherapy for Ovarian Cancer: Integrating Gene Expression Data with Machine Learning.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE:  Ovarian cancer's complexity and heterogeneity pose significant challenges in treatment, often resulting in suboptimal chemotherapy outcomes. This study aimed to leverage machine learning algorithms, gene selection, and gene expression dat...

A Scoping Review of Artificial Intelligence for Precision Nutrition.

Advances in nutrition (Bethesda, Md.)
With the role of artificial intelligence (AI) in precision nutrition rapidly expanding, a scoping review on recent studies and potential future directions is needed. This scoping review examines: 1) the current landscape, including publication venues...

Review of 2024 publications on the applications of artificial intelligence in rheumatology.

Clinical rheumatology
The integration of artificial intelligence (AI) into rheumatology has revolutionized research and clinical practice, offering transformative advancements in diagnostics, biomarker discovery, genomics, digital health technologies, and personalized med...

Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Translational psychiatry
Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and informative, the technical expertise and resources required to develop normative models may not be a...