AI Medical Compendium

FedLiverNet: a federated learning framework for privacy-preserving and efficient liver cancer detection.

Scientific reports Apr 9, 2026

Liver cancer continues to be a significant health issue on the global front, and proper segmentation of the liver and the tumor formed from the computed tomography is essential in the early diagnosis and subsequent treatment strategies. Although deep... read more

Age-grading and species identification of male mosquito Anopheles gambiae s.l. using mid-infrared spectroscopy and machine learning.

Scientific reports Apr 9, 2026

Deep learning-based high-speed railway communication systems.

Scientific reports Apr 9, 2026

High-speed railway wireless communication systems are characterized by severe Doppler shifts and fast time-varying multipath, which challenge reliable connectivity in Long-Term Evolution for Railways (LTE-R). This paper studies the two data-driven fr... read more

Physics guided fused image learning with enhanced squeeze excitation for failure analysis of multistage centrifugal pumps.

Scientific reports Apr 9, 2026

Multistage centrifugal pumps (MCPs) are critical components in industrial systems, where early and reliable fault diagnosis remains challenging due to nonstationary operating conditions, noise contamination, and limited fault sensitive information in... read more

Volatomics-based biomarkers for non-invasive diagnosis and monitoring of inflammatory bowel disease.

Journal of gastroenterology Apr 9, 2026

BACKGROUND: Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a chronic disorder that markedly impairs quality of life. Current diagnostic and monitoring tools rely on invasive procedures such as endoscopy, which ... read more

FeXAI: Federated and Explainable AI for cyber threat detection in IoT-enabled smart transportation systems.

Scientific reports Apr 9, 2026

Fusing non-textual cues with classical NLP for enhanced multimodal fake news spread detection.

Scientific reports Apr 9, 2026

The increasing spread of misinformation on social platforms has made it necessary to develop automated and accurate fake news detection systems. Traditional methods that focus solely on textual content are ineffective in dealing with more complex fak... read more

FusionLSTM-CNF: a confidence-calibrated multi-modal late fusion framework for robust stock movement prediction under uncertainty.

Scientific reports Apr 9, 2026

Explainable deep learning-based lung cancer diagnosis using clinically-guided local interpretable model-agnostic explanations.

Scientific reports Apr 9, 2026

Lung cancer remains one of the leading causes of cancer-related deaths worldwide, highlighting the urgent need for accurate and interpretable diagnostic tools. While deep learning (DL) models have achieved strong results in medical image classificati... read more

Imaging-genetics-based dementia risk prediction using deep survival neural networks in the Rotterdam Study.

Scientific reports Apr 9, 2026

Artificial Intelligence Medical Compendium

FedLiverNet: a federated learning framework for privacy-preserving and efficient liver cancer detection.

Age-grading and species identification of male mosquito Anopheles gambiae s.l. using mid-infrared spectroscopy and machine learning.

Deep learning-based high-speed railway communication systems.

Physics guided fused image learning with enhanced squeeze excitation for failure analysis of multistage centrifugal pumps.

Volatomics-based biomarkers for non-invasive diagnosis and monitoring of inflammatory bowel disease.

FeXAI: Federated and Explainable AI for cyber threat detection in IoT-enabled smart transportation systems.

Fusing non-textual cues with classical NLP for enhanced multimodal fake news spread detection.

FusionLSTM-CNF: a confidence-calibrated multi-modal late fusion framework for robust stock movement prediction under uncertainty.

Explainable deep learning-based lung cancer diagnosis using clinically-guided local interpretable model-agnostic explanations.

Imaging-genetics-based dementia risk prediction using deep survival neural networks in the Rotterdam Study.

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