Tag: Explainable AI

A machine learning framework classifies patients across three diabetes stages with 98.7% accuracy while explaining exactly which clinical variables drove ...

A new systematic review of 150 studies argues that AI-driven cybersecurity for the Industrial Internet of Things has reached impressive ...

Researchers in Thailand have developed an explainable deep learning system that diagnoses five causes of vaginal discharge from smartphone photos ...

A new study tests whether trade, governance and environmental tax indicators can classify national CO2 emission levels, and finds that ...

A 0.15-million-parameter attention-equipped neural network classifies nine wafer-map defect types with 99.88 percent accuracy on a CPU, combining latent-space augmentation ...

A systematic review maps how deep learning architectures are transforming EEG analysis for neurological disease diagnosis, while warning that data ...

Researchers have built DepressNet, an interpretable stacking-ensemble machine learning framework that stratifies depression severity into five levels from DASS-42 questionnaire ...

Machine learning and SHAP explainability reveal conditional disclosure-stability patterns across seven Palestinian banks, offering supervisors an early-warning triage tool.

A sweeping systematic review maps how explainable artificial intelligence is being applied to schizophrenia diagnosis, prognosis, and monitoring, and outlines ...

Researchers have developed and validated an AI-driven adaptive learning system that predicts student engagement, forecasts academic achievement, and generates explainable ...

A new Frontiers in Neuroinformatics article proposes FIAP®-Digital, a construct-preserving multimodal AI architecture designed to keep clinically interpretable layers visible ...

A hybrid CNN–BiLSTM network with additive attention classifies brain MRI into four Alzheimer's disease stages with 95.94% slice-level accuracy, while ...

Researchers in India have built a unified deep learning framework that classifies brain tumors in MRI scans with 98.52 percent ...

A systematic review of 83 studies finds that while deep learning models excel at ECG-based cardiovascular disease prediction, weak external ...

A Spanish research team has released FuzzyDiary, an open-source Python framework that converts univariate clinical time series into deterministic, morphology-aware ...

A systematic review and controlled validation of deep learning-based Android malware detection reveals that high benchmark accuracy masks architecture-dependent reliability ...

A new evidence-guided framework called E-MDD combines deep EEG representations, neurophysiological biomarkers, and a constrained large language model to detect ...

Researchers in Norway have developed Hjort-YOLO, a lightweight and explainable AI framework that detects wildlife from camera-trap images faster and ...

A two-stage machine learning framework can predict health insurance claim denials before submission and assign likely reason codes, achieving a ...

A multi-region computer vision framework uses YOLO detection, depth estimation and explainable AI to extract anatomical features for automated body ...