AIMC Topic: Humans

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The role of machine learning in clinical research: transforming the future of evidence generation.

Trials
BACKGROUND: Interest in the application of machine learning (ML) to the design, conduct, and analysis of clinical trials has grown, but the evidence base for such applications has not been surveyed. This manuscript reviews the proceedings of a multi-...

Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences.

Genome biology
Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. We develop a computational method, chromatin interaction neural network (ChINN), to predict chr...

Deep learning-based predictive biomarker of pathological complete response to neoadjuvant chemotherapy from histological images in breast cancer.

Journal of translational medicine
BACKGROUND: Pathological complete response (pCR) is considered a surrogate endpoint for favorable survival in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Predictive biomarkers of treatment response are crucial for guiding trea...

Identification of novel biomarkers in Hunner's interstitial cystitis using the CIBERSORT, an algorithm based on machine learning.

BMC urology
BACKGROUND:  Hunner's interstitial cystitis (HIC) is a complex disorder characterized by pelvic pain, disrupted urine storage, and Hunner lesions seen on cystoscopy. There are few effective diagnostic biomarkers. In the present study, we used the nov...

Creating efficiencies in the extraction of data from randomized trials: a prospective evaluation of a machine learning and text mining tool.

BMC medical research methodology
BACKGROUND: Machine learning tools that semi-automate data extraction may create efficiencies in systematic review production. We evaluated a machine learning and text mining tool's ability to (a) automatically extract data elements from randomized t...

A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex.

PLoS computational biology
A fundamental challenge for the theoretical study of neuronal networks is to make the link between complex biophysical models based directly on experimental data, to progressively simpler mathematical models that allow the derivation of general opera...

The "GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork": Origins, Rationale, Organization, and Prospects.

Frontiers in endocrinology
Musculoskeletal research has been enriched in the past ten years with a great wealth of new discoveries arising from genome wide association studies (GWAS). In addition to the novel factors identified by GWAS, the advent of whole-genome and whole-exo...

Inter-database validation of a deep learning approach for automatic sleep scoring.

PloS one
STUDY OBJECTIVES: Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restr...

Online evaluation method of coal mine comprehensive level based on FCE.

PloS one
An online evaluation method of coal mine comprehensive level based on Fuzzy Comprehensive Evaluation method (FCE) is proposed. Firstly, following the principles of fairness, systematicness and hierarchy, taking research and development, production, s...