Oncology/Hematology

Classifying Kidney Tumor via Adaptive SE-ResNeXt With Mutli-Novel Loss Function and Renal Mass Segmentation Using Pyramidal Attention-Based R2Unet++ Model.

Kidney tumors are one of the prevalent types of tumor globally and it has become a significant health concern. It is the most frequent type of urological tumor. While kidney tumors can present in various forms, the majority of the tumors are malignant. Hence, early detection is needed to reduce the mortality rates, develop preventive measures to minimize their impact and provide effective treatmen...

Deep Learning-Based Prediction System for Surgical Difficulty in Rectal Cancer Patients Using MRI Pelvimetry.

PURPOSE: This study presents a system that automatically predicts the difficulty of laparoscopic total mesorectal excision (TME) using magnetic resonance imaging (MRI) pelvimetry and the clinical characteristics of the patients with rectal cancer, using deep learning (DL) technology and statistical analysis. MATERIALS AND METHODS: Colorectal MRI data were collected from patients with rectal cancer...

SORBS2: A Molecular Nexus in Multisystem Diseases Through Scaffold-Mediated Regulation.

Sorbin and SH3 Domain Containing 2 (SORBS2), a multifunctional scaffold protein harbouring Sorbin homology (SoHo) and Src homology 3 (SH3) domains, se...

Clinical Significance of Biomarkers in Oropharyngeal Squamous Cell Carcinoma: Recurrence Prediction and Treatment Response.

BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) accounts for a substantial proportion of head and neck cancers, with a rising incidence larg...

Cross-attention multimodal fusion for EGFR mutation prediction: A predictive model using CT and whole-slide images.

BACKGROUND: The prediction of Epidermal Growth Factor Receptor (EGFR) mutation status in advanced lung adenocarcinoma is crucial for targeted therapy....

Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study.

OBJECTIVE: To evaluate the feasibility of cerebral computed tomography angiography (CTA) obtained with reduced iodine and low radiation at 70 kVp and ...

Deep learning for EEG-based sleep stage classification: a review.

Deep learning architectures are now widely applied in sleep electroencephalogram (EEG) analysis. These developments have significantly advanced EEG-ba...

Transcriptome-based Deep Learning Model for Predicting Gemcitabine and Cisplatin Chemotherapy Response in Urothelial Carcinoma: Development and External Validation.

BACKGROUND/AIM: Chemotherapy with gemcitabine and cisplatin remains the cornerstone of treatment for advanced urothelial carcinoma (UC), yet response ...

Current and Emerging Therapies Targeting the IL-23/IL-17 Axis in Psoriasis.

Over the past two decades, experimental and clinical evidence has established the interleukin-23 (IL-23)/interleukin-17 (IL-17) axis as a key mediator...

An integrated machine learning and computational framework with experimental validation for the identification of novel CXCR4 inhibitors.

Chemokine receptor 4 (CXCR4) is a clinically significant G protein-coupled receptor implicated in HIV-1 entry, cancer progression, immune regulation, ...

Invisible Signals, Visible Dilemmas: The Ethical Frontiers of Liquid Biopsy in Precision Oncology.

This critical review synthesizes the ethical, technical, and equity dilemmas emerging from the rapid clinical translation of liquid biopsy technologie...

CBFI: A multi-layer gene network key node identification algorithm integrating structural-biological features and dynamic regulatory weights.

OBJECTIVE: Identifying key nodes within multi-layer GRNs is crucial for uncovering potential biomarkers and therapeutic targets. Key nodes exhibit bot...

Machine learning-enhanced plasma proteomics discriminates pancreatic cancer-associated diabetes from type 2 diabetes mellitus.

Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type...

Computational and machine learning approach for nanoparticle-enhanced bio-heat transport with coupled effects of interparticle spacing and nanoparticles radius.

Targeted delivery of drugs and hyperthermia in cardiovascular disease demand the accurate delivery of nanoparticles in complex arterial geometries. Th...

Revolutionizing lung cancer screening: the rise of artificial intelligence integrating circulating tumor markers.

Lung cancer persists as the predominant oncological cause of mortality globally, underscoring an imperative public health issue that demands effective...

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature...

CT-based body composition and its change through time in relation to outcomes in participants screened for lung cancer.

BACKGROUND: Computed Tomography (CT) scans allow opportunistic evaluation of body composition. We investigated whether body composition and change thr...

Multi-scale evidence chain: Linking environmental BPA exposure to ovarian cancer through integrated omics and experimental models.

BACKGROUND: Ovarian cancer (OC) is a leading cause of female cancer mortality. Beyond genetic and reproductive risk factors, emerging evidence suggest...

Malignant Transformation Risk in Patients With Oral Leukoplakia and Type 2 Diabetes Mellitus.

INTRODUCTION AND AIMS: Oral leukoplakia (OLK) is the most common oral potentially malignant disorder, with a malignant transformation rate of up to 9....

Co-research in the development of AI and digital health tools for cancer management and care: a systematic review.

BACKGROUND: Participatory approaches (including co-research, co-design, Patient and Public Involvement [PPI], and Participatory Action Research [PAR])...