Other Cancers

The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC Cancer.

Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-...

scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing tumor heterogeneity, ye...

Predicting quality of life of patients after treatment for spinal metastatic disease: development and internal evaluation.

BACKGROUND CONTEXT: When treating spinal metastases in a palliative setting, maintaining or enhancin...

Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.

Focal adhesion kinase (FAK) is a critical drug target implicated in various disease pathways, includ...

Breast cancer detection and classification: A study on the specification and implementation of multilayer perceptron analog artificial neural networks.

Breast cancer is a leading cause of mortality worldwide. Screening therefore remains the best defens...

SGCLMD: Signed graph-based contrastive learning model for predicting somatic mutation-drug association.

Somatic mutations could influence critical cellular processes, leading to uncontrolled cell growth a...

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematolo...

Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery.

BACKGROUND AND PURPOSE: Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI...

Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohort.

PURPOSE: Information on deep learning (DL) tumor segmentation accuracy on a voxel and a structure le...

Identification of CACNB1 protein as an actionable therapeutic target for hepatocellular carcinoma via metabolic dysfunction analysis in liver diseases: An integrated bioinformatics and machine learning approach for precise therapy.

In addition to histological evaluation for nonalcoholic fatty liver disease (NAFLD), a comprehensive...

Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Cancer Detection.

: Breast cancer (BC) is the most common type of cancer in women, accounting for more than 30% of new...

Convolutional Neural Network Models for Visual Classification of Pressure Ulcer Stages: Cross-Sectional Study.

BACKGROUND: Pressure injuries (PIs) pose a negative health impact and a substantial economic burden ...

Assessing the accuracy of the GPT-4 model in multidisciplinary tumor board decision prediction.

PURPOSE: Artificial intelligence models like GPT-4 (OpenAI) have the potential to support clinical d...

Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.

Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machi...

Machine learning models for prediction of lymph node metastasis in patients with gastric cancer: a Chinese single-centre study with external validation in an Asian American population.

OBJECTIVE: To develop and validate machine learning (ML)-based models to predict lymph node metastas...

Smart nanomedicines powered by artificial intelligence: a breakthrough in lung cancer diagnosis and treatment.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due t...

Circular RNAs: driving forces behind chemoresistance and immune evasion in bladder cancer.

Bladder cancer (BCa) is characterized by recurring relapses and the emergence of chemoresistance, es...

Predictive power of artificial intelligence for malignant cerebral edema in stroke patients: a CT-based systematic review and meta-analysis of prevalence and diagnostic performance.

Malignant cerebral edema (MCE) is a severe complication of acute ischemic stroke, with high mortalit...

Prediction model of gastrointestinal tumor malignancy based on coagulation indicators such as TEG and neural networks.

OBJECTIVES: Accurate determination of gastrointestinal tumor malignancy is a crucial focus of clinic...

Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems.

Skin cancer is among the most prevalent types of malignancy all over the global and is strongly asso...

"Artificial Intelligence in NAFLD Diagnosis: A New Frontier in Managing Metastatic Prostate Cancer Risk".