Leukemia

Artificial intelligence integrated multi-omics and multimodal studies promote the efficacy of neoadjuvant chemotherapy in breast cancer: opportunities, challenges, and future perspectives.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is a critical therapeutic strategy for locally advanced breast cancer; however, its clinical utility is constrained by tumor heterogeneity and a lack of reliable predictive biomarkers. Integrating single-omics, multimodal, and multi-omics technologies provides comprehensive insights into the tumor biology, while artificial intelligence (AI) facilitates th...

P4NSU: Projection-Based Pretraining for Nonlinear Sparse Unmixing in Spectral Imaging.

Accurate quantification of components with spectral imaging (e.g., hyperspectral and Raman) is fundamentally challenged by nonlinear mixing effects. To overcome the limitations of model-specific traditional algorithms, we propose P4NSU, a deep learning framework for projection-based pretraining of nonlinear sparse unmixing. P4NSU introduces a synergistic two-part strategy: hierarchical pretraining...

Segmentation of single-cell impedance signals using deep learning: a multi-dataset study.

OBJECTIVE: Microfluidic impedance cytometry (MIC) is a high-throughput, label-free technology for single-cell analysis, with applications in cell clas...

What are the views of cancer care administrators and clinicians in England on the use of a machine learning clinical decision support system (ML-CDSS) to predict patients' risk of hepatic and renal deterioration during chemotherapy? A qualitative study.

OBJECTIVE: To explore administrators' and clinicians' views on the factors that influence their use and adoption of a machine learning clinical decisi...

Automatic computation of breast cancer biomarkers from multiple [Formula: see text] F-FDG PET image segmentation.

Neoadjuvant chemotherapy is a standard clinical practice for tumor downsizing in breast cancer, with [Formula: see text]F-FDG Positron Emission Tomogr...

Comparing the Effectiveness of Artificial Intelligence Technology with 6th Year Dental Students for the Diagnosis of Inflammatory Bone Lesions of the Mandible in Panoramic Radiography.

This study aimed to evaluate the potential role of artificial intelligence (AI) as a diagnostic support tool for inexperienced clinicians by comparing...

Early Risk Stratification for Mechanical Ventilation in Acute Ischemic Stroke: Development and Validation of a Simplified Clinical Score.

Background and PurposeMechanical ventilation (MV) occurs in a substantial subset of acute ischemic stroke (AIS) hospitalizations and is associated wit...

Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.

OBJECTIVE: Radiogenomics aims to non-invasively predict tumour genotypes from imaging, but most studies assume molecular homogeneity by assigning a si...

An interpretable PET/CT-based radiomic-clinical model for predicting bone marrow involvement in follicular lymphoma: comparison of pelvic and spine-pelvis VOI frameworks.

PURPOSE: To investigate the feasibility of non-invasively identifying bone marrow involvement (BMI) in follicular lymphoma (FL) using baseline 18F-FDG...

Breaking glycolysis: allosteric hotspots for multi-target drug repurposing.

Glycolysis is essential for cellular energy production, making its enzymes attractive antimicrobial targets. Traditional strategies targeting conserve...

Data modeling the interplay between single-cell shape, single-cell protein expression, and tissue state.

While cell shape fundamentally governs tissue function, the underlying links between single-cell shape and protein expression have been difficult to r...

Prognostic value of estimated pulse wave velocity for all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic (CKM) syndrome: analyses of NHANES 2007-2018.

BACKGROUND: The impact of estimated pulse wave velocity (ePWV) on the prognosis of cardiovascular-kidney-metabolic (CKM) syndrome has not been explore...

Retinal biological age correlates with bone mineral density and fracture risk score and predicts incident osteoporosis.

Osteoporosis often lacks accessible screening tools, leading to underdiagnosis and increased fracture risk. We explored the potential of a retinal agi...

Identification of drug candidates against glioblastoma with machine learning and high-throughput screening of heterogeneous cellular models.

Glioblastoma multiforme (GBM) is an aggressive primary brain tumour that presents significant treatment challenges due to its complex pathology and he...

Droplet microfluidic profiling of NK cell cytotoxicity with machine learning-enabled target-cell death analysis.

Predicting the clinical efficacy of Natural Killer (NK) cell immunotherapies remains challenging due to functional heterogeneity within effector popul...

EEG-Based Clustering Shows Distinct Separation of Chronic Pain Patients Before Spinal Cord Stimulation Surgery.

Chronic pain is associated with disrupted cortical activity, yet individual variability in these neural patterns remains poorly understood. Electroenc...

Hemovigilance in a Brazilian Amazon blood center: A temporal analysis of 5-year consumption patterns.

BACKGROUND: The transfusion of blood components remains a cornerstone in the management of hematological and onco-hematological diseases. Effective bl...

Developing and validating an electronic health record-embedded AI model for managing multimorbid hospitalisation risk in patients with chronic RESpiratory disease (AiRES): a study protocol.

BACKGROUND: Chronic respiratory diseases (CRDs), such as asthma and chronic obstructive pulmonary disease (COPD), are heterogeneous conditions with a ...

A predictive 14-gene signature and FLI1 inhibition overcome tumor-infiltrating lymphocyte dysfunction in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype lacking effective targeted therapies. Although immune checkpoint inhibitors such as pemb...

A comparative analysis in a clinical cohort: multiple imputation by chained equations and a novel super learner-based imputation approach.

BACKGROUND: Missing data is a challenge in clinical research, especially in real-world data (RWD), where complete case analysis can bias results and r...