AI Medical Compendium Topic:
Biomarkers, Tumor

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Application of machine learning to large in-vitro databases to identify cancer cell characteristics: telomerase reverse transcriptase (TERT) expression.

Oncogene
Advances in biotechnology and machine learning have created an enhanced environment for unearthing and exploiting previously unrecognized relationships between genomic and epigenetic data with potential therapeutic implications. We applied advanced a...

Ultrasensitive detection of circulating tumour DNA via deep methylation sequencing aided by machine learning.

Nature biomedical engineering
The low abundance of circulating tumour DNA (ctDNA) in plasma samples makes the analysis of ctDNA biomarkers for the detection or monitoring of early-stage cancers challenging. Here we show that deep methylation sequencing aided by a machine-learning...

Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer.

Journal of clinical pathology
Clinical workflows in oncology depend on predictive and prognostic biomarkers. However, the growing number of complex biomarkers contributes to costly and delayed decision-making in routine oncology care and treatment. As cancer is expected to rank a...

Evaluating machine learning methodologies for identification of cancer driver genes.

Scientific reports
Cancer is driven by distinctive sorts of changes and basic variations in genes. Recognizing cancer driver genes is basic for accurate oncological analysis. Numerous methodologies to distinguish and identify drivers presently exist, but efficient tool...

The case for AI-driven cancer clinical trials - The efficacy arm in silico.

Biochimica et biophysica acta. Reviews on cancer
Pharmaceutical agents in oncology currently have high attrition rates from early to late phase clinical trials. Recent advances in computational methods, notably causal artificial intelligence, and availability of rich clinico-genomic databases have ...

The human-in-the-loop: an evaluation of pathologists' interaction with artificial intelligence in clinical practice.

Histopathology
AIMS: One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and...

The usefulness of CanAssist breast in the assessment of recurrence risk in patients of ethnic Indian origin.

Breast (Edinburgh, Scotland)
Accurate recurrence risk assessment in hormone receptor positive, HER2/neu negative breast cancer is critical to plan precise therapy. CanAssist Breast (CAB) assesses recurrence risk based on tumor biology using artificial intelligence-based approach...

Data-driven approaches to advance research and clinical care for pediatric cancer.

Biochimica et biophysica acta. Reviews on cancer
Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with adult cancer. Multi-omics profiling of retrospective and prospective cohorts coupled with innovative computational analysis have been instrumental in u...

Improvement of Neoantigen Identification Through Convolution Neural Network.

Frontiers in immunology
Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are lim...