Other Cancers

A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.

OBJECTIVES: With the popularization of chest computed tomography (CT) screening, there are more sub-...

Improving radiomics reproducibility using deep learning-based image conversion of CT reconstruction algorithms in hepatocellular carcinoma patients.

OBJECTIVES: CT reconstruction algorithms affect radiomics reproducibility. In this study, we evaluat...

Data-driven decision-making for precision diagnosis of digestive diseases.

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented o...

An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea.

Automatic deep-learning models used for sleep scoring in children with obstructive sleep apnea (OSA)...

Groundwork for AI: Enforcing a benchmark for neoantigen prediction in personalized cancer immunotherapy.

This article expands on recent studies of machine learning or artificial intelligence (AI) algorithm...

MRI-Based Radiomics and Deep Learning in Biological Characteristics and Prognosis of Hepatocellular Carcinoma: Opportunities and Challenges.

Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading cause of ca...

AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.

PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-...

A Novel Deep Learning Algorithm for Human Papillomavirus Infection Prediction in Head and Neck Cancers Using Routine Histology Images.

The etiology of head and neck squamous cell carcinoma (HNSCC) involves multiple carcinogens, such as...

Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT.

PURPOSE: To investigate the performance of deep learning and radiomics features of intra-tumoral reg...

Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial.

BACKGROUND: The role of computer-aided detection in identifying advanced colorectal neoplasia is unk...

Real-Time Computer-Aided Detection of Colorectal Neoplasia During Colonoscopy : A Systematic Review and Meta-analysis.

BACKGROUND: Artificial intelligence computer-aided detection (CADe) of colorectal neoplasia during c...

Prediction of central lymph node metastasis based on deep learning models for patients with clinically node-negative papillary thyroid carcinoma.

Artificial intelligence and the blood film: Performance of the MC-80 digital morphology analyzer in samples with neoplastic and reactive cell types.

INTRODUCTION: Implementing artificial intelligence-based instruments in hematology laboratories requ...

Evaluating Autoencoders for Dimensionality Reduction of MRI-derived Radiomics and Classification of Malignant Brain Tumors.

Malignant brain tumors including parenchymal metastatic (MET) lesions, glioblastomas (GBM), and lymp...

Predicting Lymph Node Metastasis From Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathologic Images.

We developed a deep learning framework to accurately predict the lymph node status of patients with ...

Tumor necrosis factor-alpha, transforming growth factor-beta, degree of lower urinary tract symptoms as predictors of erectile dysfunction in benign prostatic hyperplasia patients.

OBJECTIVE: Erectile dysfunction (ED) is a condition of insufficient penile erection, consistently or...

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination.

Proteins play a crucial role in many biological processes, where their interaction with other protei...

Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) micro...

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medi...

An overview of ultrasound-derived radiomics and deep learning in liver.

Over the past few years, developments in artificial intelligence (AI), especially in radiomics and d...

Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.

PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced ...