COVID-19

PickAMoo: LIDAR-enhanced mask R-CNN segmentation for precision weight estimation in dairy cattle using smartphone imaging.

Data on body weight, as well as objective measures of body condition and size, are essential for appropriate decision-making on farm level, for example in calculations of nutrient requirements, health monitoring, and breeding-related assessment. Weighing dairy cattle and assessing their body condition are labour-intensive and are therefore often not performed as frequently as desired under practic...

Application Value of a nomogram integrating contrast-enhanced CT radiomics and clinical indicators in evaluating lymph node metastasis in pediatric peripheral neuroblastoma.

OBJECTIVE: To construct a machine learning model using contrast-enhanced CT radiomics and clinical indicators, aiming to improve the diagnostic accuracy for lymph node metastasis in children with peripheral neuroblastoma and provide practical evidence for clinical diagnosis and treatment. METHODS: A total of children with pathologically confirmed neuroblastoma were retrospectively enrolled between...

Clinically reliable and stable automated segmentation of DLBCL lesions on PET/CT using self-configuring nnU-Net for robust TMTV quantification.

PURPOSE: Accurate lesion segmentation on 18F-FDG PET/CT is essential for the effective management of Diffuse Large B-cell Lymphoma (DLBCL). While deep...

Domain adaptive uplift modeling across heterogeneous mental health cohorts.

Predicting who will deteriorate under stress is important for targeting mental-health support; yet, treatment-effect models are rarely tested across p...

The Evolution of Precision Anti-Doping From UGT2B17 Polymorphism Insights to Integrated Detection Frameworks.

Screening for endogenous anabolic-androgenic steroid abuse has long relied on the urinary testosterone/epitestosterone (T/E) ratio. However, this metr...

Deciphering the multi-target mechanism of Magnolia officinalis in irritable bowel syndrome with diarrhea: A combined network pharmacology, machine learning, and in vivo validation study.

BACKGROUND: The bark of Magnolia officinalis Rehder & E. Wilson, used in TCM for abdominal distension, pain, and diarrhea, aligns with IBS-D symptoms....

Phage ImmunoPrecipitation sequencing (PhIP-Seq) in autoimmunity research: From high-resolution epitope mapping to multi-omics integration.

Autoimmune diseases (AIDs) affect 5-10% of the global population, yet effective diagnosis and treatment remain challenging due to their complexity and...

Adaptive Disorder as the Hallmark of Nanobodies Antigen-Binding Loops.

Nanobodies are antigen-binding proteins of great interest as diagnostics and therapeutics. Accurate and fast characterization of their complementarity...

Dual sagittal-guided coarse-to-fine rib segmentation and numbering in chest CT.

Rib identification in chest CT is time-consuming and labor-intensive, as clinicians repetitively examine hundreds of CT slices to pinpoint a certain r...

Automated deep learning model for predicting pathological complete response in rectal cancer: A tool to organ-preserving strategies.

BACKGROUND: Accurate identification of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal canc...

Integrative transcriptomic analysis identifies immune-associated candidate genes and altered immune cell infiltration in pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a progressive vascular disease characterized by immune dysregulation and pulmonary vascular remod...

Decoding the role of polyamine metabolism in lung adenocarcinoma prognosis: A triangulated approach combining transcriptome, single-cell and Mendelian randomization analyses.

The progression of lung adenocarcinoma (LUAD) is influenced by polyamine metabolism, which modulates antitumor immunity, although the underlying mecha...

Radiomics analysis of restaging MRI for detection of pathological complete response in locally advanced rectal cancer.

PURPOSE: magnetic resonance imaging (MRI)-based radiomics has emerged as a promising approach for non-invasive prediction of treatment response in rec...

Deep Learning-Based Prediction of Pathogenicity for ABL1 Protein Variants Using Sequence Representation.

The ABL1 gene encodes a non-receptor tyrosine kinase implicated in leukemia and other genetic disorders. This study presents a deep learning-based app...

Classifying Clinical Evidence Levels of Cancer Variants in Biomedical Literature Using Machine Learning and Large Language Models.

Automating the classification of clinical evidence levels in biomedical literature can support precision oncology by facilitating the acceleration of ...

Machine learning-assisted clone selection for intensified cell culture processes.

Intensified fed-batch processes are becoming increasingly prevalent among biomanufacturers due to their superior space-time yields relative to traditi...

Upregulation of the Mitophagy-Related Gene EXOSC4 Is Associated with Immune Dysregulation in Spinal Cord Injury.

Spinal cord injury (SCI) profoundly impairs patients' quality of life and imposes a substantial economic burden on society, often resulting in irrever...

Experimental and Computational Approaches to Identify Noncoding Pathogenic Variation in Rare Disease.

Noncoding variants occur within noncoding genes as well as within the regulatory nontranslated regions of protein-coding genes. It is important to be ...

Enhancing respiratory virus surveillance among hospitalised children: a machine learning-based predictive model.

BACKGROUND: Viral respiratory tract infections (vRTIs) are a leading cause of paediatric hospitalisation and healthcare utilisation. Existing syndromi...

Identifying and validating ITGB2 and HNRNPAB as diagnostic biomarkers in chronic obstructive pulmonary disease using bioinformatics and Integrated Machine Learning Methods.

BACKGROUND AND AIM: COPD is a common respiratory disease characterized by progressive airflow restriction that severely affects patients' quality of l...