AIMC Topic: Neoplasms

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Unveiling anticancer peptides; from the mechanisms of action to their development through artificial intelligence.

European journal of pharmacology
Cancer is a leading cause of death worldwide and a major burden on the healthcare system. Current treatment methods are limited as they have low selectivity, unspecific targeting and increasing multidrug resistance. Therefore, newer modes of therapeu...

Minimizing and quantifying uncertainty in AI-informed decisions: Applications in medicine.

Proceedings of the National Academy of Sciences of the United States of America
AI is now a cornerstone of modern dataset analysis. In many real world applications, practitioners are concerned with controlling specific kinds of errors, rather than minimizing the overall number of errors. For example, biomedical screening assays ...

Predicting cancer risk using machine learning on lifestyle and genetic data.

Scientific reports
Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. This study investigates the application of Machine Learning (ML) techniques to predict cancer...

A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells.

Nature communications
DNA replication stress is a hallmark of cancer that is exploited by chemotherapies. Current assays for replication stress have low throughput and poor resolution whilst being unable to map the movement of replication forks genome-wide. We present a n...

Multiphysics modelling enhanced by imaging and artificial intelligence for personalised cancer nanomedicine: Foundations for clinical digital twins.

Journal of controlled release : official journal of the Controlled Release Society
Nano-sized drug delivery systems have emerged as a more effective, versatile means for improving cancer treatment. However, the complexity of drug delivery to cancer involves intricate interactions between physiological and physicochemical processes ...

Telomere-targeted medicine: Bridging molecular mechanisms and clinical applications in age-related diseases.

Life sciences
Telomeres, the nucleoprotein structures at the ends of chromosomes, have emerged as critical regulators of cellular aging and key contributors to the pathogenesis of age-related diseases. This comprehensive review examines the evolution of telomere b...

Building simplified cancer subtyping and prediction models with glycan gene signatures.

Cell reports methods
We identified a gene panel comprising 71 glycosyltransferases (GTs) that alter glycan patterns on cancer cells as they become more virulent. When these cancer-pattern GTs (CPGTs) were run through an algorithm trained on The Cancer Genome Atlas, they ...

Ligand supplementation restores the cancer therapy efficacy of the antirheumatic drug auranofin from serum inactivation.

Nature communications
Auranofin, an FDA-approved antirheumatic gold drug, has gained ongoing interest in clinical studies for treating advanced or recurrent tumors. However, gold ion's dynamic thiol exchange nature strongly attenuates its bioactivity due to the fast forma...

Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1/PD-L1: a retrospective study.

BMC medical informatics and decision making
BACKGROUND: Anti-programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunotherapy has revolutionized cancer treatment. However, it can cause immune-related adverse events, including acute kidney injury (AKI). Such adverse e...

Integrating mHealth Innovations into Decentralized Oncology Trials.

Journal of medical systems
The integration of mobile health (mHealth) technologies into decentralized clinical trials (DCTs) may represent a paradigm shift in oncology research, offering innovative solutions to longstanding challenges in clinical trial design and execution. mH...