AIMC Topic: Machine Learning

Clear Filters Showing 14051 to 14060 of 34417 articles

Digital Histopathology by Infrared Spectroscopic Imaging.

Annual review of analytical chemistry (Palo Alto, Calif.)
Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy w...

Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness.

Scientific reports
There is a growing piece of evidence that artificial intelligence may be helpful in the entire prostate cancer disease continuum. However, building machine learning algorithms robust to inter- and intra-radiologist segmentation variability is still a...

Sequence similarity governs generalizability of de novo deep learning models for RNA secondary structure prediction.

PLoS computational biology
Making no use of physical laws or co-evolutionary information, de novo deep learning (DL) models for RNA secondary structure prediction have achieved far superior performances than traditional algorithms. However, their statistical underpinning raise...

Nonparametric failure time: Time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures.

Biometrics
Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that could provide erroneous predictions when the effects of covariates are complex. Modern advances in computational hardware have led to an increasing inter...

Brain Tumor Classification Using Deep Neural Network and Transfer Learning.

Brain topography
In the field of medical imaging, the classification of brain tumors based on histopathological analysis is a laborious and traditional approach. To address this issue, the use of deep learning techniques, specifically Convolutional Neural Networks (C...

Usefulness of machine learning softwares to screen titles of systematic reviews: a methodological study.

Systematic reviews
OBJECTIVE: To investigate the usefulness and performance metrics of three freely-available softwares (Rayyan®, Abstrackr® and Colandr®) for title screening in systematic reviews.

A comparison of ChatGPT-generated articles with human-written articles.

Skeletal radiology
OBJECTIVE: ChatGPT (Generative Pre-trained Transformer) is an artificial intelligence language tool developed by OpenAI that utilises machine learning algorithms to generate text that closely mimics human language. It has recently taken the internet ...

Recent advances in predicting and modeling protein-protein interactions.

Trends in biochemical sciences
Protein-protein interactions (PPIs) drive biological processes, and disruption of PPIs can cause disease. With recent breakthroughs in structure prediction and a deluge of genomic sequence data, computational methods to predict PPIs and model spatial...

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis.

Journal of biomedical informatics
OBJECTIVE: Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to identi...

Learning From Experience and Finding the Right Balance in the Governance of Artificial Intelligence and Digital Health Technologies.

Journal of medical Internet research
Artificial intelligence (AI) and machine learning medical tools have the potential to be transformative in care delivery; however, this change will only be realized if accompanied by effective governance that ensures patient safety and public trust. ...