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Adaptive dual-modality neuromodulation for chronic pain and muscle dysfunction: real-world insights from the NXTSTIM™ EcoAI digital platform.

BACKGROUND: Chronic musculoskeletal pain is often inadequately managed with pharmacologic therapy. A...

Contextualizing the Patient Blood Management (PBM) Program Through the Lens of Bioethical Principles.

In an increasingly specialized medical landscape, Patient Blood Management (PBM) has emerged as a mu...

Ferritin and transferrin predict common carotid intima-media thickness in females: a machine-learning informed individual participant data meta-analysis.

Cardiovascular toxicity of ethyl maltol exposure: a comprehensive investigation from virtual screening to experimental validation.

Ethyl maltol is a ubiquitous synthetic flavor enhancer. Despite its widespread use in foods, beverag...

Investigating cognitive fatigue recovery through mechanical massage and binaural beats: An AI-driven fNIRS study.

Cognitive fatigue is a state of reduced mental performance resulting from prolonged periods of cogni...

A machine learning approach to predicting dyspnea with noninvasive biomarkers.

Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in pat...

DPA-Net: A dual-path attention neural network for estimating glycemic metrics from self-monitored blood glucose data.

Continuous glucose monitoring (CGM) provides dense and dynamic glucose profiles that enable reliable...

Smart hydrogels for overcoming cancer multidrug resistance.

Multidrug resistance (MDR) remains the principal impediment to curative oncology, driven by complex ...

Baseline pain, fatigue, and sleep quality predict 12-week pain improvement in inflammatory arthritis: retrospective real-world analysis of a digital health application cohort.

UNLABELLED: Despite advances in pharmacotherapy, many patients with inflammatory arthritis (IA) expe...

Excited-State-Guided Molecular Design System for Type I Photosensitizers.

Type I photosensitizers (PSs), which generate Type I reactive oxygen species (ROS) through the elect...

Machine-learning classification of motor unit types in the adult mouse.

Motor unit diversity arises from differences in the contractile properties of muscle fibres and the ...

Co-occurrence patterns of malnutrition indicators among children in sub-Saharan Africa.

BACKGROUND: Despite progress towards SDG2, malnutrition remains a major concern. Little is known abo...

Integrated multi-omics and experimental validation for identifying novel biomarkers of acute myocardial infarction.

Acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality, and early diag...

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep State Classification.

OBJECTIVE: Fetal sleep state classification is essential for identifying neurodevelopmental complica...

Towards noninvasive blood count using a deep learning pipeline from bulbar conjunctiva videos.

Invasive venous blood draws remain the clinical standard for hematology, yet they are invasive, time...

Prediction of post-COVID chronic fatigue syndrome using data mining and machine learning techniques in Isfahan COVID cohort study.

BACKGROUND: Post-COVID Fatigue (PCF) is one of the most common issues people face after recovering f...

ProVenTL: a transfer-learning framework for predicting peptide-protein interactions derived from snake venom for cancer therapeutics.

Accurate prediction of peptide-protein interactions (PepPI) is crucial for advancing peptide-based a...

A Conversational Platform (Okaya) for Multimodal Digital Biomarkers of Fatigue, Cognition, and Mental Health: Feasibility Observational Study.

BACKGROUND: Collection of multimodal data (video, audio, and text) can yield digital biomarkers rele...

Fetal pHocus: A Novel Approach to Non-Invasive Fetal Arterial Blood pH Assessment via Near-Infrared Spectroscopy.

Modern intrapartum fetal health assessments are currently limited to monitoring heart rate and spati...

LDIE-FDNet: Lightweight dynamic image enhancement-enabled real-time fatigue driving detection network.

Aiming at the imbalance between accuracy and real-time of existing fatigue driving detection models,...

A Machine learning framework for calf muscle fatigue assessment using IMU sensors and EMG-Based labeling.

PURPOSE: Calf muscle fatigue detection is essential for sports performance monitoring, injury preven...