Oncology/Hematology

Differentiating adenocarcinoma and squamous cell carcinoma in lung cancer using semi automated segmentation and radiomics.

INTRODUCTION: Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are frequently observed forms of non-small cell lung cancer (NSCLC), playing a significant role in global cancer mortality. This research categorizes NSCLC subtypes by analyzing image details using computer-assisted semi-automatic segmentation and radiomic features in model development.

Advances and Integrations of Computer-Assisted Planning, Artificial Intelligence, and Predictive Modeling Tools for Laser Interstitial Thermal Therapy in Neurosurgical Oncology.

Laser interstitial thermal therapy (LiTT) has emerged as a minimally invasive, MRI-guided treatment of brain tumors that are otherwise considered inoperable because of their location or the patient's poor surgical candidacy. By directing thermal energy at neoplastic lesions while minimizing damage to surrounding healthy tissue, LiTT offers promising therapeutic outcomes for both newly diagnosed an...

Non-invasive prediction of NSCLC immunotherapy efficacy and tumor microenvironment through unsupervised machine learning-driven CT Radiomic subtypes: a multi-cohort study.

BACKGROUND: Radiomics analyzes quantitative features from medical images to reveal tumor heterogeneity, offering new insights for diagnosis, prognosis...

Preoperative Assessment of Lymph Node Metastasis in Rectal Cancer Using Deep Learning: Investigating the Utility of Various MRI Sequences.

PURPOSE: This study aimed to develop a deep learning (DL) model based on three-dimensional multi-parametric magnetic resonance imaging (mpMRI) for pre...

AI-based large-scale screening of gastric cancer from noncontrast CT imaging.

Early detection through screening is critical for reducing gastric cancer (GC) mortality. However, in most high-prevalence regions, large-scale screen...

Diagnostic Study of Head and Neck Metastatic Tumors From Different Primary Sites Based on Stacking Machine Learning Methods.

Metastatic tumors of the head and neck (MTHN) typically indicate advanced disease with a poor prognosis, originating from cells that spread from other...

Patient acceptability of CITOBOT for cervical cancer screening: A mixed-method study.

This study assessed the acceptability of CITOBOT, a device for early cervical cancer screening in a real-world pilot setting as part of a translationa...

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionall...

Clinical benefits of deep learning-assisted ultrasound in predicting lymph node metastasis in pancreatic cancer patients.

AIM: This study aimed to develop and validate a deep learning radiomics nomogram (DLRN) derived from ultrasound images to improve predictive accuracy ...

Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance.

BACKGROUND: Breast cancer is one of the most common malignant tumors, threatening women's health and life globally. Despite significant treatment adva...

Machine Learning Model for Predicting Sertraline-like Activities and Its Impact on Cancer Chemosensitization.

Selective serotonin reuptake inhibitors (SSRIs) like sertraline are crucial in treating depression and anxiety disorders, and studies indicate their p...

Development of the treatment prediction model in the artificial intelligence in depression - medication enhancement study.

We introduce an artificial intelligence model to personalize treatment in major depression, which was deployed in the Artificial Intelligence in Depre...

Palmitoylation regulators drive the progression of clear cell renal cell carcinoma through Inhibition of cuproptosis: insights into the role of ZDHHC18.

BACKGROUND: Protein palmitoylation is a reversible post-translational modification that increases protein hydrophobicity, which can affect protein loc...

CellMemory: hierarchical interpretation of out-of-distribution cells using bottlenecked transformer.

Machine learning methods, especially Transformer architectures, have been widely employed in single-cell omics studies. However, interpretability and ...

[Incidental pulmonary nodules on CT imaging: what to do?].

Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage) lung cancers without any signs or symptoms. These...

A model developed by machine learning and principal component analysis for predicting bronchiolitis obliterans syndrome after allogeneic HSCT in a Chinese population with hematologic malignancies.

Bronchiolitis obliterans syndrome (BOS) is a severe pulmonary complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), w...

MRI Radiomics and Automated Habitat Analysis Enhance Machine Learning Prediction of Bone Metastasis and High-Grade Gleason Scores in Prostate Cancer.

RATIONALE AND OBJECTIVES: To explore the value of machine learning models based on MRI radiomics and automated habitat analysis in predicting bone met...

Hyperspectral Imaging Combined With Deep Learning for Precision Grading of Clear Cell Renal Cell Carcinoma.

This study presents an integrated approach combining hyperspectral imaging (HSI) and deep learning for accurate grading of clear cell renal cell carci...

Axial Skeletal Assessment in Osteoporosis Using Radiofrequency Echographic Multi-spectrometry: Diagnostic Performance, Clinical Utility, and Future Directions.

Osteoporosis, a prevalent skeletal disorder, necessitates accurate and accessible diagnostic tools for effective disease management and fracture preve...

The impact of artificial intelligence on the endoscopic assessment of inflammatory bowel disease-related neoplasia.

Inflammatory bowel disease (IBD) is a group of chronic inflammatory conditions of the gastrointestinal tract resulting from an inappropriate immune re...