Anemia

Physics-guided GNN-transformer model for multi-scale fatigue life prediction of concrete track slabs in high-speed railways.

This study establishes a novel machine learning paradigm integrating physical mechanisms. It aims to address the limitations of traditional methods in predicting the concrete fatigue life of high-speed railway (HSR) track slab, particularly their insufficient accuracy and poor interpretability due to overlooking microstructure characteristics and load randomness. The research method innovatively d...

A deep state-space analysis framework for cancer patient latent state estimation and classification from EHR time-series data.

Advancements in deep learning technologies and an increase in medical data have enhanced the accuracy of disease diagnosis and treatment strategies. Notably, significant progress has been made in the use of deep learning-based time-series prediction models for short-term disease onset prediction and analysis of important features. However, research on explainable deep learning for long-term diseas...

Redefining obstructive sleep apnea diagnosis: An attention augmented CNN-BiLSTM hybrid alternative to traditional PSG testing.

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by repeated episodes of upper airway obstruction during sleep. Despite its heal...

Tomek links-based SMOTE method for class imbalance in blood cell classification with dual path sliding window attention model.

Medical image processing has transformed the Complete Blood Count (CBC) analysis to enhance diagnostic accuracy and to detect diseases such as neurode...

Implementation of electronic patient-reported outcomes in supportive care for oncology patients.

PURPOSE OF REVIEW: Patient-reported outcomes (PROs) have become increasingly important in oncology, capturing the patient perspective on symptoms, tre...

An integrative clinical and bioinformatic analysis identifies MicroRNAs as biomarkers of ischemic stroke severity.

Identifying reliable circulating biomarkers is crucial for improving the diagnosis and risk stratification of patients with ischemic stroke. In this s...

Modulating subjective and objective cognitive state fatigue in long COVID with repetitive anodal tDCS: results from a double-blinded randomized controlled trial.

BACKGROUND: Cognitive fatigue is a frequently reported and debilitating symptom of long COVID, yet effective therapeutic interventions remain limited....

Novel bayesian nonparametric unsupervised learning approach to precision symptom management in cancer survivors: a re-analysis of a comparative effectiveness trial.

Cancer survivors often experience multiple cooccurring symptoms such as insomnia, pain, fatigue, and anxiety; yet conventional analyses in symptom sci...

The challenge in finding a simple, accurate, reliable, and affordable tool for the objective assessment of excessive daytime sleepiness (EDS).

Excessive daytime sleepiness (EDS) refers to a physiological state where individuals have difficulty remaining alert during the day. Managing EDS is p...

A P4HA2 hypoxia signature derived from single cell atlas stratifies conserved subtypes with prognostic significance in cervical squamous cell carcinoma.

Identification of hypoxia- and mitophagy-related diagnostic biomarkers for ulcerative colitis based on bioinformatic analysis and machine learning.

BACKGROUND: Ulcerative colitis (UC) is a chronic nonspecific inflammatory bowel disease of unknown etiology that is associated with a significant risk...

Performance validation of a closed loop fully automated AI model for lung nodule stratification in screening cases.

BACKGROUND: Several limitations hinder the effectiveness of human-based lung cancer screening (LCS): high false-positive rates leading to unnecessary ...

Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood...

The effect of air pollution and household environmental indicators on anemia status among under-five children in low-middle income countries: exploring potential machine learning applications on demographic and health surveys.

Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in ...

OLink proteomic biomarker to predict clinical efficacy of Macaranga sinensis Müll.Arg: A nested case-control study.

ETHNOPHARMACOLOGICAL RELEVANCE: Despite the fact that herbal medicine has been used for a long time, their clinical application is challenged by uncle...

[Computerized intrapartum cardiotocography: current evidence, controversies, and future directions].

Cardiotocography (CTG) is defined as the simultaneous recording of fetal heart rate and uterine contractions. It is used worldwide during labour to as...

Integrating multi-omics and machine learning systematically deciphers cellular heterogeneity and fibrotic regulatory networks in the progression from MASLD to MASH.

The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic dysfunction-associated steatohepatitis (MASH) is a ...

Mechanical behaviour of additively manufactured metals.

Additive manufacturing is reshaping the production of engineering components in diverse industries, such as the automotive, aerospace, defence and bio...

Multifunctional conductive hydrogel based on carboxymethyl cellulose/oxidized sodium alginate for machine learning-guided sports training.

Multifunctional hydrogels have shown great promise in advanced wearable sensing technologies; however, their performance under real-world sweaty and d...

Robust multimodal mental workload classification: A cross-physiological condition machine learning approach.

BACKGROUND AND OBJECTIVE: Aircraft pilots can be faced with a high mental workload (MW) combined with moderate hypoxia and sleep restriction. We aimed...