AIMC Topic: Machine Learning
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CNN based method for classifying cervical cancer cells in pap smear images.
Scientific reports
Jul 4, 2025
The absence of reliable early treatment serves as one of the main causes of cervical cancer. Hence, it is crucial to detect cervical cancer early. The biggest challenge in diagnosing cervical cancer early is that it is asymptomatic until it develops ...
Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms.
Scientific reports
Jul 4, 2025
Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each year worldwide. The mortality rate is over 251,000 deaths annually (IARC, 2020 reports). Detecting BTs is complex because they vary in nature. Early diag...
A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.
Scientific reports
Jul 4, 2025
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co...
Leveraging pathological markers of lower grade glioma to predict the occurrence of secondary epilepsy, a retrospective study.
Scientific reports
Jul 4, 2025
Epilepsy is a common manifestation in patients with lower grade glioma (LGG), often presenting as the initial symptom in approximately 70% of cases. This study aimed to identify clinical and pathological markers for epileptic seizures in patients wit...
Integrating AI predictive analytics with naturopathic and yoga-based interventions in a data-driven preventive model to improve maternal mental health and pregnancy outcomes.
Scientific reports
Jul 4, 2025
Maternal mental health during pregnancy is a crucial area of research due to its profound impact on both maternal and child well-being. This paper proposes a comprehensive approach to predicting and monitoring psychological health risks in pregnant w...
Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.
Science advances
Jul 4, 2025
Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor samples from 149 Chinese patients with breast cancer across ERHER2, ERHER2, and ERHER2 subtypes, cat...
Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Jul 4, 2025
Trait Genome-to-Phenome (G2P) dimensionality and "breeding context" combine to influence the realised prediction skill of different whole genome prediction (WGP) methods. Theory and empirical evidence both suggest there is likely to be "No Free Lunch...
Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.
Renal failure
Jul 3, 2025
Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk of infection, presenting significant clinical, and economic challenges. Identifying predictive bioma...
Identification of key genes as diagnostic biomarkers for IBD using bioinformatics and machine learning.
Journal of translational medicine
Jul 3, 2025
BACKGROUND: The pathogenesis of inflammatory bowel disease (IBD) involves complex molecular mechanisms, and achieving clinical remission remains challenging. This study aims to identify IBD-potential biomarkers, analyze their correlation with immune ...
The value of triglyceride-glucose index-related indices in evaluating migraine: perspectives from multi-centre cross-sectional studies and machine learning models.
Lipids in health and disease
Jul 3, 2025
BACKGROUND: This study employed representative data from the U.S. and China to delve into the correlation among migraine prevalence, the triglyceride‒glucose index, a marker of insulin resistance, and the composite indicator of obesity.
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