Other Cancers

The accuracy of artificial intelligence in the diagnosis of soft tissue sarcoma: A systematic review and meta-analysis.

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer.

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative ...

Role of oxidative balance score in staging and mortality risk of cardiovascular-kidney-metabolic syndrome: Insights from traditional and machine learning approaches.

OBJECTIVES: To evaluate the roles of oxidative balance score (OBS) in staging and mortality risk of ...

Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.

Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor...

Interstitial-guided automatic clinical tumor volume segmentation network for cervical cancer brachytherapy.

Automatic clinical tumor volume (CTV) delineation is pivotal to improving outcomes for interstitial ...

Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images.

Whole-body bone scan (WBS) is usually used as the effective diagnostic method for early-stage and co...

Deep Augmented Metric Learning Network for Prostate Cancer Classification in Ultrasound Images.

Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrec...

Syn-Net: A Synchronous Frequency-Perception Fusion Network for Breast Tumor Segmentation in Ultrasound Images.

Accurate breast tumor segmentation in ultrasound images is a crucial step in medical diagnosis and l...

StackTHP: A stacking ensemble model for accurate prediction of tumor-homing peptides in cancer therapy.

The tumor-homing peptides (THPs) have emerged as one of the attractive resources for targeted cancer...

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to...

Impact of [F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role.

Lung cancer remains one of the most prevalent cancers globally and the leading cause of cancer-relat...

Efficient Brain Tumor Detection and Segmentation Using DN-MRCNN With Enhanced Imaging Technique.

This article proposes a method called DenseNet 121-Mask R-CNN (DN-MRCNN) for the detection and segme...

Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.

BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellul...

Discovery of mutations predictive of survival benefit from immunotherapy in first-line NSCLC: A retrospective machine learning study of IMpower150 liquid biopsy data.

Predictive biomarker identification in cancer treatment has traditionally relied on pre-defined anal...

Identification of novel diagnostic and prognostic microRNAs in sarcoma on TCGA dataset: bioinformatics and machine learning approach.

The discovery of unique microRNA (miR) patterns and their corresponding genes in sarcoma patients in...

Automated Electrical Detection of Proteins for Oral Squamous Cell Carcinoma in an Integrated Microfluidic Chip Using Multi-Frequency Impedance Cytometry and Machine Learning.

Proteins can act as suitable biomarkers for the prognosis and diagnosis of certain conditions and ca...

Prediction of Lymph Node Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images With Size on CT and PET-CT Findings.

BACKGROUND AND OBJECTIVE: Echo features of lymph nodes (LNs) influence target selection during endob...

Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC.

BACKGROUND: Immune checkpoint inhibitors (CPIs) have revolutionized cancer therapy for several tumor...

Machine learning analysis identified NNMT as a potential therapeutic target for hepatocellular carcinoma based on PCD-related genes.

Programmed cell death (PCD) plays a critical role in cancer biology, influencing tumor progression a...

The Extent to Which Artificial Intelligence Can Help Fulfill Metastatic Breast Cancer Patient Healthcare Needs: A Mixed-Methods Study.

The Artificial Intelligence Patient Librarian (AIPL) was designed to meet the psychosocial and suppo...

Advances of artificial intelligence in clinical application and scientific research of neuro-oncology: Current knowledge and future perspectives.

Brain tumors refer to the abnormal growths that occur within the brain's tissue, comprising both pri...