AIMC Topic: Machine Learning

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Machine learning-based prediction of glioma grading.

PloS one
OBJECTIVE: Gliomas are among the most common and heterogeneous primary tumours of the central nervous system. Accurate grading is essential for treatment planning and prognosis, yet conventional histopathological approaches are limited by subjectivit...

Data-Driven Machine Learning Framework for the Regulation of Protein Adsorption on Surfaces.

Langmuir : the ACS journal of surfaces and colloids
Protein adsorption on surfaces is a highly complex process, governed by intricate interactions between protein, surface and surrounding environment. However, accurately predicting protein adsorption amounts and precisely controlling adsorption behavi...

Coupling Machine Learning with Clusterization-Triggered Emission for Geographical Origin Tracing of Rice.

Analytical chemistry
Tracing the geographical origin of rice is of great significance in protecting the rights and interests of consumers and legitimate producers, as well as ensuring food safety. Here, we propose the combination of machine learning (ML) and clustering-t...

Mechanics of small intestine motility for oral macromolecular delivery: modelling segmentation versus peristalsis.

Drug delivery
Intestinal motility, including peristalsis and segmentation, drives complex fluid movements critical for the oral delivery of biologics and other macromolecules. Despite advances, oral delivery remains commercially limited by low bioavailability, oft...

A machine-learning informed circulating microbial DNA signature for early diagnosis of esophageal adenocarcinoma.

Gut microbes
Esophageal adenocarcinoma (EAC) has seen a dramatic rise in incidence in developed countries over the past three decades. Early detection of its precursors-gastroesophageal reflux disease (GERD), Barrett's esophagus (BE), and high-grade dysplasia (HG...

Development and validation of an interpretable Random Forest model for predicting recurrence after endoscopic submucosal dissection in superficial oesophageal squamous cell carcinoma.

Annals of medicine
BACKGROUND: Currently, endoscopic submucosal dissection (ESD) has become the preferred treatment for superficial oesophageal squamous cell carcinoma (SESCC). However, due to the residual background mucosa, some patients are still at risk of postopera...

GenEEG: Improving epileptic EEG detection through patient-adaptive latent diffusion and continual learning.

Computers in biology and medicine
Automated seizure detection systems face significant challenges due to the limited availability of clinical EEG data, a substantial class imbalance between seizure and non-seizure recordings, considerable variability among patients, and the issue of ...

Advancing PFAS Detection through Machine Learning Prediction of F NMR Spectra.

Environmental science & technology
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants with diverse structures. To further advance the impact assessment and remediation technology for PFAS pollution, new approaches for identifying emerging PFAS are neces...

A heart rate variability-driven framework for depression screening leveraging emotion-elicited autonomic divergence.

Journal of physiological anthropology
OBJECTIVE: Depression manifests significant emotional dysregulation, characterized by heightened sadness susceptibility and attenuated happiness responsiveness in individuals with depression (IWD). This study employs structured emotion induction prot...

Epileptic spasm recognition: EEG classification using time-frequency features and machine learning.

Biomedical engineering online
Epileptic spasm (ES), characterized by sudden muscle contractions and loss of consciousness, poses significant challenges in early diagnosis and treatment, especially in infants and young children. Despite advances in EEG-based seizure detection, the...