Oncology/Hematology

FOSL2 drives transcriptional activation of super‑enhancer-regulated DYNC1H1 to promote hypoxia‑induced oral squamous cell carcinoma progression.

Hypoxia is a hallmark of oral squamous cell carcinoma (OSCC) and plays a critical role in driving tumor progression. However, the mechanisms by which OSCC cells respond to hypoxic signaling to promote malignant phenotypes remain unclear. The present study aimed to identify the key regulatory factors governing hypoxic adaptation in OSCC. Based on bulk RNA‑sequencing (RNA‑seq) data from The Cancer G...

Artificial Intelligence in Oncology: Clinical Applications, Challenges, and Opportunities.

Artificial intelligence (AI) is reshaping cancer research and clinical oncology by enabling large-scale analysis of complex biomedical data. Although early AI efforts focused on single-modality tasks such as imaging interpretation or pathology classification, contemporary oncology increasingly requires integrated reasoning across heterogeneous inputs, including imaging, digital pathology, and geno...

Proteomic and transcriptomic analyses identify the role of RBM25 in the malignant progression of glioma.

Glioma is a primary tumor derived from central nervous system glial cells. RNA binding motif protein 25 (RBM25) has been implicated in glioma progress...

Vasoactive intestinal peptide associated 8-gene signature with prognostic and immune associations in melanoma.

Vasoactive intestinal peptide (VIP) plays a multifaceted role in cancer biology, yet its prognostic and immunological implications in melanoma remain ...

From Technological Innovation to Clinical Translation: Progress and Challenges in 3D Bioprinting for the Development of Breast Cancer Bone Metastasis Models.

The construction of 3D in vitro tumor models centered on bioprinting technology represents one of the most anticipated interdisciplinary innovations a...

Two-stage deep learning networks for diagnosing and staging membranous glomerulonephritis from electron microscopy images.

PURPOSE: The purpose of this study was to use transmission electron miscroscopy images to develop a deep-learning-based artificial intelligence model ...

Metabolic interactions of host-gut microbiota: Shaping the future of precision diagnosis and therapeutic discovery in gastrointestinal cancers.

This collection of reviews and research articles highlights the diagnostic and therapeutic potential of gut microbial metabolites across various gastr...

Deep Learning-Based Diagnosis of Parotid Gland Tumors on CT Images: A Multi-view Approach for Preoperative Differentiation of Benign and Malignant Lesions.

BACKGROUND: Accurate preoperative differentiation between benign and malignant parotid gland tumors is essential for guiding surgical planning and tre...

Predictors of warfarin therapeutic dose in cancer patients: a preliminary comparative study using machine learning-integrated explainable artificial intelligence and Bayesian models.

BACKGROUND: Warfarin dosing in cancer patients is challenging due to altered pathophysiology and variable responses. While machine learning offers pre...

Artificial Intelligence for Sleep Instability and Motor Phenotyping: Clinical Translation Beyond Sleep Staging.

Sleep medicine has rapidly adopted artificial intelligence, but most applications still prioritize automated sleep staging or single summary indices, ...

A macrophage-related efferocytosis-based two-gene prognostic model for acute myeloid leukemia identified by multi-omics and machine learning.

Background Acute myeloid leukemia (AML) remains a lethal hematologic malignancy with high heterogeneity. Macrophage-mediated efferocytosis in the tumo...

Towards an accessible, centralised, searchable database for AI courses in Europe: the Artificial Intelligence in Medical Imaging and Radiation Oncology Education (AIMIROE) project.

OBJECTIVE: Artificial intelligence (AI) is transforming medical imaging and radiation oncology, yet limited understanding and access to education hind...

Innovative strategies for early detection of cardiotoxicity: artificial intelligence and multi-modality collaborative models.

Cancer therapeutics account for a significant proportion of new drug development, reflecting advances in diagnosis, treatment, and disease control. Ho...

Development and External Validation of a Machine Learning-Based Risk Classification Score for Prostate Cancer-Specific Cardiovascular Risk.

PURPOSE: Patients with prostate cancer (PC) face elevated cardiovascular (CV) risk. Conventional CV risk scores are often poorly calibrated for PC and...

A recurrent interferon, stress, and survival axis identifies a rare malignant programme across glioblastoma single-cell, spatial, and longitudinal cohorts.

Glioblastoma exhibits profound intratumoral heterogeneity and rapid adaptation under stress, complicating durable therapeutic control. Here, a biologi...

Enhancing brain tumor classification with a simplified CNN through hyperparameter optimization.

Brain tumors remain a major public health challenge because of their high mortality rate and the need for timely and accurate diagnosis. Magnetic Reso...

AI-MIRACLE: Artificial Intelligence and MultIpaRAmetric MRI Predict CLinical OutcomEs to Neoadjuvant Immunotherapy in Patients with Muscle-invasive Bladder Cancer Undergoing Radical Cystectomy.

BACKGROUND AND OBJECTIVE: Neoadjuvant immune-checkpoint inhibitors (ICIs) in muscle-invasive bladder cancer (MIBC) were tested in patient's ineligible...

Ethnicity-specific molecular subtypes and a machine-learning risk model in Asian patients with non-muscle-invasive bladder cancer.

Non-muscle-invasive bladder cancer (NMIBC) has high rates of recurrence and progression, yet its molecular landscape across different ethnicities rema...

Machine learning based approaches for structure activity relationship analysis of heparanase inhibitors.

Human Heparanase (HPSE), the only mammalian endo-β-D-glucuronidase, plays an important role in extracellular matrix remodeling and the release of hepa...

A multimodal interpretable deep learning-radiomics framework for predicting lymph node metastasis following neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter validation study.

Accurate assessment of lymph node metastasis (LNM) following neoadjuvant chemoradiotherapy (nCRT) presents a significant clinical challenge and is ess...