Oncology/Hematology

Lung cancer as a global health challenge: Multidimensional biomarker research and therapeutic advances.

Lung cancer, the leading cause of global cancer-related mortality, is categorized into small-cell and non-small-cell subtypes. The heterogeneous non-small-cell lung cancer group is further subcategorized primarily into adenocarcinoma, squamous cell carcinoma, and large cell carcinoma, each underpinned by distinct molecular alterations. Although traditional serum biomarkers aid in subtype different...

Immune-activated & pathology-characterized: the distinct clear cell renal cell carcinoma subtypes for 3PM strategies derived from artificial intelligence in multi-omics.

BACKGROUND AND OBJECTIVE: Renal clear cell carcinoma (ccRCC) is highly heterogeneous, with significant differences in clinical outcomes such as prognosis and sensitivity to target therapy. The development of predictive, preventive, and personalized medicine (3PM) strategies in the area is essential to execute personalized treatment for ccRCC patients against disease progression effectively. WORKIN...

Hulled Rice or husk? Synchrotron radiation XRF and deep learning approach for the determination of the geographical origin of Chinese rice samples.

Accurate authentication of rice geographical origin is crucial for food safety and fraud prevention. Synchrotron radiation X-ray fluorescence (SR-XRF)...

MuTriM: A multiscale deep learning model integrating longitudinal radiomics and pathomic features for predicting recurrence and adjuvant radiation benefit in breast cancer.

PURPOSE: We present MuTriM, a multimodal deep learning model integrating DCE-MRI and whole-slide pathology to predict survival and radiation benefit i...

Development and temporal validation of an interpretable point score for in-hospital mortality in CLL/SLL using the U.S. National Inpatient Sample, 2016-2022.

In-hospital mortality among patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) is ∼6%, yet no validated, transparent beds...

Integrative transcriptomic and machine learning analysis identifies core immune genes and pathways driving graft-versus-host disease after allogeneic hematopoietic stem cell transplantation.

BACKGROUND: Graft-versus-host disease (GVHD), a major adverse event following allogeneic hematopoietic stem cell transplantation (allo-HSCT), commonly...

Based on WGCNA and machine learning studies, SMURF2 drives NSCLC malignant transformation, ferroptosis, and macrophage polarization by ubiquitinating SPP1.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with poor prognosis and high mortality in advanced stages. Although sec...

Olfactomedin 1 acts as a tumor suppressor in glioblastoma: integrated analysis and mechanistic prediction.

Glioblastoma (GBM) is an aggressive brain tumor with a poor prognosis, yet its molecular mechanisms remain incompletely understood. Olfactomedin 1 (OL...

AI in the Prediction of Hepatic Fibrosis Progression Using Non-Coding RNAs.

Hepatic fibrosis is a dynamic and progressive condition that can lead to cirrhosis and hepatocellular carcinoma (HCC) if left untreated. Appropriate a...

Cardiogenic Shock Revisited: From Hemodynamic-Centric to Multimodal Precision Care.

Cardiogenic shock (CS) remains a major clinical challenge, with persistently high short-term mortality despite advances in reperfusion therapy, pharma...

Machine Learning Algorithm for Nanomedicine: AI Curated Nanocarriers for Cancer Treatment.

Cancer remains a major global health challenge due to its genetic variability and intricate molecular mechanisms, which complicate the development of ...

Cross-cancer survival prediction using machine learning models.

Among the many challenges faced by healthcare systems, cancer remains one of the most urgent. This makes the application of artificial intelligence a ...

AI caption generation model for digital pathology of adenocarcinoma in endoscopic histopathology using multi-instance attention mechanisms.

AI knowledge, attitudes, perceptions, and willingness to use AI among oncologists in China: a nationwide cross-sectional study.

BACKGROUND: The integration of artificial intelligence (AI) into healthcare, particularly in oncology, has attracted considerable attention in China. ...

Detection of Lung and Colon Cancer Using XRx-Net With Histopathological Images.

Lung and Colon Cancer (LCC) is a prevalent type of cancer influenced by factors such as genetics, smoking, second-hand smoke exposure, and alcohol con...

Predicting the Postoperative Recurrence Risk in Soft-Tissue Sarcomas of the Extremities and Trunk Using MRI-Based Nomogram.

RATIONALE AND OBJECTIVES: This study aims to develop a comprehensive nomogram for predicting the 3-year recurrence risk of patients with soft-tissue s...

Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma.

BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which ca...

Estimating the Individualized Effect of Tooth Extraction before Radiotherapy on Osteoradionecrosis Using Causal Machine Learning.

The purpose of this study was to determine the average treatment effect (ATE) of tooth extraction before radiotherapy on the risk of osteoradionecrosi...

From Multimodal Data to Clinical Insight: An Explainable Model for Preoperative Salivary Gland Lesion Diagnosis.

OBJECTIVE: To develop and validate a multimodal dual-step support vector machine model (SVM-DualNet) for the preoperative three-class classification o...

RAS signaling in lung adenocarcinoma is defined by lineage context and DUSP4 loss.

BACKGROUND: The molecular landscape of lung adenocarcinoma (LUAD) is often illustrated as a driver-oncogene "pie chart," but identical mutations exhib...