Oncology/Hematology

Survival Prediction in Patients With Bladder Cancer Undergoing Radical Cystectomy Using a Machine Learning Algorithm: Retrospective Single-Center Study.

BACKGROUND: Traditional statistical models often fail to capture the complex dynamics influencing survival outcomes in patients with bladder cancer after radical cystectomy, a procedure where approximately 50% of patients develop metastases within 2 years. The integration of artificial intelligence (AI) offers a promising avenue for enhancing prognostic accuracy and personalizing treatment strateg...

AI-assisted cryo-dose estimation and tissue injury modeling for assessing side effects in MRI-guided prostate cryoablation: a retrospective study.

Focal therapy offers a middle ground between active surveillance and whole-gland treatment for patients with low- and intermediate-risk prostate cancer, aiming to eliminate tumor tissue while preserving surrounding structures. Among available focal therapy approaches, MRI-guided focal cryoablation offers some technical advantages, including real-time monitoring of iceball formation and intrao...

CSF proteomics identifies ADGRG1 as a predictive biomarker of intrathecal immune checkpoint inhibitor response in leptomeningeal metastasis.

BACKGROUND: Leptomeningeal metastasis (LM) is a fatal complication of advanced cancer with limited therapeutic options and poor prognosis. Immune chec...

Hybrid deep neural network with PCA based features optimization for enhancing brain tumor classification.

Brain tumors have been an important medical concern. This is primarily due to their growth patterns have been hard to predict and their medical needs ...

FOXK1 induced upregulation of KIF20A promotes hepatocellular carcinoma progression via Wnt/β-Catenin/EMT signaling.

Liver cancer ranks sixth in incidence and third in mortality worldwide, with hepatocellular carcinoma (HCC) accounting for 90% of cases. Kinesin famil...

BreasTransNeXt: An Enhanced Multi-Module Vision Transformer For Early Breast Cancer Diagnosis.

Breast cancer (BC) represents the most common and one of the most lethal malignancies among women globally, ranking second only to lung cancer in term...

The consensus molecular subtypes of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) lacks a standardized classification system, resulting in inconsistent clinical management and a suboptimal p...

AdaptiveInvolutionNet: Spatially-adaptive involution with channel-wise attention for breast MRI tumor classification.

BACKGROUND: Early and accurate classification of breast tumors from MRI scans is essential for improving patient outcomes. However, a key limitation o...

Design and development of a convolutional neural network based on human cognitive attention mechanism for automatic classification of leukemia.

Cancer occurs when healthy cells in the body grow abnormally and out of control. Leukemia is a type of cancer that affects White Blood Cells (WBCs) an...

Prediction of Symptomatic Radiation Pneumonitis in Lung Cancer Patients: A Radiomics and Dosiomics Machine Learning Approach Using the Prospective Multicenter RTOG 0617 and REQUITE Trials.

PURPOSE: Radiation-induced pneumonitis (RP) is a side effect after thoracic radiation therapy (RT). The ability to predict RP would facilitate treatme...

In silico discovery and biological evaluation of a novel selective HDAC8 inhibitor featuring 1H-pyrazolo[3,4-b]pyridine scaffold.

Histone deacetylase 8 (HDAC8), a pivotal epigenetic regulator orchestrating chromatin remodeling and transcriptional control, has emerged as a compell...

Uncovering the silent invaders: Dormant tumour cells in the brain microenvironment.

Brain metastasis remains a lethal clinical challenge, largely driven by dormant tumour cells (DTCs). This reversible quiescent state enables dissemina...

KRT15 identified by scRNA-Seq and machine learning as stemness regulator and prognostic biomarker in ESCC.

Postoperative recurrence and metastasis in esophageal squamous cell carcinoma (ESCC) are closely associated with cancer stem cells (CSCs), though the ...

The value of artificial intelligence combined with multimodal data analysis in tumor immunotherapy and targeted therapy.

The advent of immunotherapy and targeted therapy has revolutionized oncology treatment in recent years, marking a transformative shift toward precisio...

The role of artificial intelligence in pre-operative prediction of completeness of cytoreduction for peritoneal surface malignancies: a scoping review.

BACKGROUND: Complete cytoreduction is the most important prognostic factor for patients with peritoneal surface malignancies (PSM) and its prediction ...

Oncogenic function and transcriptional dynamics of MYCN in liver tumorigenesis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. It is often diagnosed at advanced stages and characterized by high recu...

Novel Lipid Nanoparticle (LNP) Delivery Systems Enabling the Advancement of RNA Therapeutics.

Lipid nanoparticle (LNP)-mRNA technology has profoundly transformed the biomedical landscape, establishing itself as a highly versatile and powerful p...

Multiharmonic imaging-based automated recognition of cutaneous T-cell lymphoma.

BACKGROUND: Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of non-Hodgkin lymphomas, with mycosis fungoides (MF) being the most common t...

Carbon dot nanoparticles as multifunctional fluorescent probes: from tunable synthesis to biomedical applications.

Carbon dots (CDs) have emerged as highly promising fluorescent nanomaterials due to their exceptional optical properties, biocompatibility, and facile...

Where New and Old Technologies Converge: In Search of a Better Way to Predict Pathologic Fracture: Commentary on an article by Shinn Kim, MD, et al.: "Deep Learning Model for Differentiating Between Neoplastic Pathologic Fracture and Nonpathologic Fracture Using Hip Radiographs".