AI Medical Compendium

A hybrid approach for citrus disease detection using convolutional neural networks and fuzzy inference systems for enhanced accuracy and interpretability.

Scientific reports May 20, 2026

The citrus diseases are affecting the fruit production worldwide thereby posing an economical burden. Major research is moving towards finding solutions using Artificial Intelligence (AI) and Image processing methods. Due to factors like illumination... read more

A parallel convolutional neural network with background removal and lesion segmentation for field plant disease severity classification.

Scientific reports May 20, 2026

Today, the intelligent automation of agriculture has received much attention from researchers. One of the important factors for the success of this automation is the timely diagnosis of plant disease and making a decision appropriate to the existing ... read more

A reproducible benchmark of QRS detection algorithms across diverse ECG datasets and noise conditions.

Scientific reports May 20, 2026

Accurate R-peak detection in electrocardiograms is critical for heart rate monitoring, heart rate variability analysis, and cardiac condition diagnosis. However, reliable detection remains challenging in real-world scenarios due to noise, artifacts, ... read more

Exergoeconomic and machine learning approach to optimal PV siting under diverse climatic conditions.

Scientific reports May 20, 2026

The performance and economic viability of utility-scale photovoltaic (PV) plants are critically influenced by location-specific climatic factors, yet conventional site selection often overlooks thermodynamic quality and long-term degradation. This st... read more

A hybrid deep learning model with adaptive feature fusion for automated rice leaf disease detection and classification.

Scientific reports May 20, 2026

Many countries greatly rely on agriculture as a means of livelihood and economic growth. Even the most industrialized countries need food, medicine, clothing, and shelter produced by crops. Rice is one of the most significant and widely grown crops w... read more

A temporal keyword co-occurrence network mining framework for detecting structural transitions in cancer biomarker research (2006-2023).

Scientific reports May 20, 2026

Biomarker research for cancer diagnosis and prognosis has rapidly expanded technologically and thematically, along with advancements in molecular diagnostics, liquid biopsy, immunotherapy, and artificial intelligence (AI)-based technologies. However,... read more

Multicenter machine learning model for assessing the impact of malignancy on in-hospital mortality in heart failure patients: a clinical decision support system with interpretable artificial intelligence.

Scientific reports May 20, 2026

Heart failure (HF) and malignancy represent two major global health burdens that frequently coexist and lead to poor clinical outcomes. However, the specific impact of malignancy on in-hospital mortality in HF patients remains incompletely understood... read more

Multi-task adversarial learning detects intersectional algorithmic bias in AI recruitment systems.

Scientific reports May 20, 2026

With the widespread application of artificial intelligence in recruitment, algorithmic bias issues have become increasingly prominent, seriously threatening social fairness and job seekers' rights. Addressing the limitations of existing bias detectio... read more

A residual-learning MMSE neural detector for 6G MIMO-OTFS systems under diverse channel conditions.

Scientific reports May 20, 2026

Orthogonal time-frequency space modulation combined with multiple-input multiple-output transmission (MIMO-OTFS) has emerged as a strong waveform candidate for sixth-generation (6G) wireless networks because of its robustness against high mobility an... read more

Explainable convolutional neural network model provides an alternative genome-wide association perspective on mutations in SARS-CoV-2.

Scientific reports May 20, 2026

Identifying informative genomic features in SARS-CoV-2 can help clarify patterns of viral evolution. In this study, we developed an explainable convolutional neural network (CNN) model to classify SARS-CoV-2 genomic sequences into the WHO-designated ... read more

Artificial Intelligence Medical Compendium

A hybrid approach for citrus disease detection using convolutional neural networks and fuzzy inference systems for enhanced accuracy and interpretability.

A parallel convolutional neural network with background removal and lesion segmentation for field plant disease severity classification.

A reproducible benchmark of QRS detection algorithms across diverse ECG datasets and noise conditions.

Exergoeconomic and machine learning approach to optimal PV siting under diverse climatic conditions.

A hybrid deep learning model with adaptive feature fusion for automated rice leaf disease detection and classification.

A temporal keyword co-occurrence network mining framework for detecting structural transitions in cancer biomarker research (2006-2023).

Multicenter machine learning model for assessing the impact of malignancy on in-hospital mortality in heart failure patients: a clinical decision support system with interpretable artificial intelligence.

Multi-task adversarial learning detects intersectional algorithmic bias in AI recruitment systems.

A residual-learning MMSE neural detector for 6G MIMO-OTFS systems under diverse channel conditions.

Explainable convolutional neural network model provides an alternative genome-wide association perspective on mutations in SARS-CoV-2.

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Artificial Intelligence Medical Compendium

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