AIMC Topic: Machine Learning

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Using machine learning for chemical-free histological tissue staining.

Journal of histotechnology
Hematoxylin and eosin staining can be hazardous, expensive, and prone to error and variability. To circumvent these issues, artificial intelligence/machine learning models such as generative adversarial networks (GANs), are being used to 'virtually' ...

Machine learning applications in craniosynostosis diagnosis and treatment prediction: a systematic review.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Craniosynostosis refers to the premature fusion of one or more of the fibrous cranial sutures connecting the bones of the skull. Machine learning (ML) is an emerging technology and its application to craniosynostosis detection and management is under...

Explicate molecular landscape of combined pulmonary fibrosis and emphysema through explainable artificial intelligence: a comprehensive analysis of ILD and COPD interactions using RNA from whole lung homogenates.

Medical & biological engineering & computing
Combined pulmonary fibrosis and emphysema (CPFE) presents a unique challenge in respiratory disorders, merging features of interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD). Using the random forest algorithm, our study ...

An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.

Computers in biology and medicine
OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Yet premature discontinuation undermines treatment effectiveness, increasing the risk of mortality and overdose. We developed and evaluated a machine l...

Integrated Bioinformatics and Machine Learning Analysis Identify ACADL as a Potent Biomarker of Reactive Mesothelial Cells.

The American journal of pathology
Mesothelial cells with reactive hyperplasia are difficult to distinguish from malignant mesothelioma cells based on cell morphology. This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma c...

Plasma Steroid Profiling Combined With Machine Learning for the Differential Diagnosis in Mild Autonomous Cortisol Secretion From Nonfunctioning Adenoma in Patients With Adrenal Incidentalomas.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: To assess the diagnostic value of combining plasma steroid profiling with machine learning (ML) in differentiating between mild autonomous cortisol secretion (MACS) and nonfunctioning adenoma (NFA) in patients with adrenal incidentalomas.

Developing an interpretation model for body fluid identification.

Forensic science international
Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenar...

Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles.

Computers in biology and medicine
Distant metastasis of cancer is a significant contributor to cancer-related complications, and early identification of unidentified stomach adenocarcinoma is crucial for a positive prognosis. Changes inDNA methylation are being increasingly recognize...

ORDerly: Data Sets and Benchmarks for Chemical Reaction Data.

Journal of chemical information and modeling
Machine learning has the potential to provide tremendous value to life sciences by providing models that aid in the discovery of new molecules and reduce the time for new products to come to market. Chemical reactions play a significant role in these...

Impact of long-term mining activity on groundwater dynamics in a mining district in Xinjiang coal Mine Base, Northwest China: insight from geochemical fingerprint and machine learning.

Environmental science and pollution research international
Long-term coal mining could lead to a serious of geo-environmental problems. However, less comprehensive identification of factors controlling the groundwater dynamics were involved in previous studies. This study focused on 68 groundwater samples co...