Other Cancers

Molecular characteristics and modifications of glioblastoma affecting the efficacy of immunotherapy.

Glioblastoma is a highly aggressive brain tumor characterized by complex genetic, molecular, and epigenetic features that present significant challenges for treatment. This review explores recent advances in understanding the molecular and epigenetic landscape of glioblastoma, with particular emphasis on epigenetic modifications such as DNA methylation, histone changes, and N6-methyladenosine regu...

Artificial intelligence-guided analysis of the tumor microenvironment predicts response to pembrolizumab in rare tumors.

BACKGROUND: Pathologic tumor response and changes in the tumor microenvironment (TME) predict outcomes to immune checkpoint inhibitors, but are understudied in rare tumors. We investigated whether artificial intelligence (AI)-powered analyses of pretreatment and on-treatment biopsies may inform treatment outcomes to pembrolizumab. METHODS: We evaluated 256 baseline and 248 on-treatment biopsies fr...

PANTHER Challenge Report: Cross-Domain Pancreatic Tumor Segmentation in Magnetic Resonance Imaging.

Accurate delineation of pancreatic tumors on Magnetic Resonance Imaging (MRI) is important for diagnosis, radiotherapy treatment planning, and outcome...

Efficacy and safety of multiple treatments for small hepatocellular carcinoma: an updated systematic review and component network meta analysis.

BACKGROUND: This is an updated component network meta-analysis to evaluate efficacy and safety of various therapeutic approaches and their combination...

Using machine learning algorithms based on laboratory indicators to establish a diagnostic model for lung cancer.

BACKGROUND: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Current diagnostic strategies rely primarily on imagi...

Single-model deep learning approach for simultaneous cervical vertebral maturation staging and skeletal jaw relationship on lateral cephalograms using YOLOv8 and CNN.

BACKGROUND: This study aimed to develop an integrated artificial intelligence (AI) pipeline for cervical vertebral maturation (CVM) staging and skelet...

Multi-omics integration and clinical validation identify CKAP2 as a diagnostic biomarker for bladder cancer.

BACKGROUND: Bladder cancer (BC) remains a prevalent malignancy with a high recurrence rate; however, the lack of specific biomarkers hinders early det...

Genetically engineered outer membrane vesicles as next-generation bionanomaterials for therapeutic and diagnostic applications.

Outer membrane vesicles (OMVs), naturally released by Gram-negative bacteria, represent a unique class of bionanomaterials with inherent immunogenicit...

Tumor-naïve ctDNA detection with deep learning-enhanced error suppression for sensitive mutation calling.

BACKGROUND: Circulating tumor DNA (ctDNA) detection offers minimally invasive monitoring of cancer from blood samples. While tumor-informed approaches...

Artificial Intelligence-Driven MRI for Cervical Nodal Metastasis Detection in Oral Squamous Cell Carcinoma: A Hierarchical Meta-Analysis of Diagnostic Accuracy.

BACKGROUND: Artificial intelligence (AI) applied to magnetic resonance imaging (MRI) may improve detection of cervical lymph node metastases in oral s...

Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.

BACKGROUND: Lysosomes are essential for intracellular degradation and recycling, and changes in their function significantly contribute to tumor growt...

Machine learning applications in the detection and treatment of esophageal cancer.

Esophageal cancer (EC) is a gastrointestinal malignancy associated with a poor prognosis worldwide. It is characterized by an insidious onset, marked ...

From Magnetic Resonance Imaging Radiomics to the Prediction of Regional Nodal Metastasis in Laryngeal Cancer.

OBJECTIVE: To investigate the potential of magnetic resonance imaging (MRI) radiomics-based machine learning (ML) models in predicting local lymph nod...

Improved Detection of Lentigo Maligna with AI-Assisted Dermoscopy: A Reader Study in Facial Pigmented Lesions.

BACKGROUND: Differentiating lentigo maligna (LM) from benign facial pigmented lesions remains difficult due to substantial clinical and dermoscopic ov...

Identification and validation of BLK and OSBPL10 as diagnostic and prognostic biomarkers for nasopharyngeal carcinoma through machine learning algorithms.

Despite substantial advances in radiotherapy and chemotherapy for nasopharyngeal carcinoma (NPC), a subset of patients still develops metastasis or re...

AI-Based Opportunistic CT Risk Assessment Using TotalSegmentator in Osteoporotic Vertebral Fractures.

Osteoporotic vertebral fractures impair quality of life and increase both morbidity and mortality, yet they are largely preventable. Routine CT examin...

Comparative 10-year performance of mammography artificial intelligence, polygenic, and clinical breast cancer risk models in the Kaiser Permanente Research Bank.

BACKGROUND: We compared performance across 3 breast cancer risk domains-clinical, polygenic, and mammography artificial intelligence-alone and in comb...

Mechanobiology of the tumor microenvironment: a review of therapeutic interactions and in vitro elasticity measurement techniques.

The stiffness of the extracellular matrix (ECM) regulates cellular behavior, influencing tumor progression and therapeutic resistance. In cancer, aber...

Development and validation of a machine learning-based postoperative staging system for hilar cholangiocarcinoma: a retrospective single-center cohort study.

BACKGROUND: Hilar cholangiocarcinoma (HCCA) is a malignant tumor at the hepatic hilum with poor prognosis and survival despite surgical resection. Whi...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...