Oncology/Hematology

Lower odds of prevalent vertebral fractures with b/tsDMARD use among rheumatoid arthritis patients in clinical remission: a retrospective observational study.

OBJECTIVES: This study investigated serum pentosidine levels as an advanced glycation end product (AGE)-related marker of bone matrix deterioration and examined the association between b/tsDMARD use and prevalent vertebral fractures in patients with RA in clinical remission. METHODS: Seventy-six patients with RA in clinical remission (DAS28-CRP < 2.3) were included. Serum pentosidine, bone turnove...

[Artificial intelligence as decision support tool in urological oncology: current evidence and challenges].

BACKGROUND: The rising incidence of cancer, increasing life expectancy and complex personalized treatment concepts pose considerable challenges for the healthcare system. Artificial intelligence (AI)-in particular machine learning (ML), deep learning (DL), and large language models (LLMs)-offers promising potential for supporting therapeutic decisions in urological oncology. OBJECTIVE: The aim of ...

Artificial intelligence in pancreatic cancer: applications in early detection, tumor staging, and survival prediction-a comprehensive review.

In the rapidly developing world, artificial intelligence (AI) is one of the emerging applications in the medical domain. Early detection of cancer is ...

Semen RNA-Based Biomarkers for Prostate Cancer Detection and Risk Stratification: A Prospective Multi-Center Validation Study.

OBJECTIVE: To assess the diagnostic performance of semen RNA-based biomarkers for detecting prostate cancer and differentiating cancer grade groups. M...

The Integration of Artificial Intelligence in Radiation Medical Physics: Insights from an International Survey with Regional Variability.

BACKGROUND: Artificial intelligence (AI) is considered to be a leading technology in radiation medical physics, which has the potential for improving ...

Personalized machine learning-guided radiation dose escalation in newly diagnosed glioblastoma: prospective pilot study.

Glioblastoma is a highly aggressive primary brain tumor with near-universal recurrence despite maximal safe resection followed by standard chemoradiat...

YOLO-LS: a novel deep learning framework for brain tumor segmentation in Magnetic Resonance Imaging.

Brain tumors exhibit high heterogeneity in morphology, texture, and location, making accurate recognition and segmentation critical for clinical diagn...

Multimodal interpretable deep learning for transcriptome-informed precision oncology and drug mechanism analysis.

Precision oncology faces critical challenges in interpreting complex cellular signals and predicting drug responses across heterogeneous cancer enviro...

Single-cell and deep learning identify hypoxia-responsive lncRNAs predicting outcomes in colorectal cancer.

Emerging evidence highlights hypoxia-responsive long non-coding RNAs (lncRNAs) as potential modulators in tumor biology. In this study, we explored th...

Generative adversarial networks-based Image-to-Image translation allows tumor consistency prediction from standard MR images in pituitary adenomas.

Generative adversarial networks (GANs) offer potential in cross-modality image translation, but their application in pituitary adenomas remains uncert...

Decoding (digital) histopathology: The building blocks for computational researchers.

Computational Pathology is a novel discipline at the intersection of pathology and computer science, driven by the recent advances in machine learning...

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...

Trustworthy artificial intelligence in predictive medicine: cancer survival analysis using ethical-by-design and explainable artificial intelligence models.

OBJECTIVES: This study aims to develop and evaluate a trustworthy and ethical-by-design machine learning (ML) framework for predicting 5-year cancer s...

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...

Deep residual network fusing CT images and clinical variables to predict lung adenocarcinoma aggressiveness.

BACKGROUND: Lung adenocarcinoma presenting as ground-glass nodules (GGNs) comprises three invasive subtypes (adenocarcinoma in situ [AIS], minimally i...

Application of a multimodal MRI model integrating radiomics and habitat features for predicting glioma pathology and prognosis.

BACKGROUND: Accurate grading and prognostic assessment of glioma requires integrating key molecular biomarkers, including IDH mutation status and the ...

Machine learning-based study of breath sounds in children with asthma in remission and cough variant asthma.

BACKGROUND: Traditional auscultation, heavily dependent on the subjective judgment of physicians, can lead to variability in diagnoses. This study aim...

Benchmarking large language models in breast cancer care: agreement with radiology-led multidisciplinary tumor board decisions.

BACKGROUND: Multidisciplinary tumor boards (MDTBs) play a central role in breast cancer management by integrating imaging findings with clinical and p...

Copper transporters promote the malignant progression of glioblastoma by regulating the immunosuppressive tumour microenvironment via the SLC31A1-WNT5A axis.

BACKGROUND: The prognosis for patients with glioblastoma (GBM) remains extremely poor, a challenge largely attributable to the complex nature of its m...

Model-guided design of lymphatic drug delivery systems using osmotic pressure, viscosity and lymph node size.

Metastatic lymph nodes (LNs) represent a major barrier to effective drug delivery in cancer therapy. To address this challenge, a lymphatic drug deliv...