Oncology/Hematology

Development and validation of a combined nomogram model based on deep learning contrast-enhanced ultrasound and clinical factors to predict preoperative aggressiveness in pancreatic neuroendocrine neoplasms.

OBJECTIVES: This study aimed to develop and validate a combined nomogram model based on deep learnin...

Robot-Assisted Right Colectomy with Sequential Wedge Resection of Segments 4 and 5 of The Liver and Cholecystectomy for Colon Cancer with Metastasis to The Liver.

The liver is the most common place for colon adenocarcinoma metastasis because of portal circulation...

A content-based image retrieval system for the diagnosis of lymphoma using blood micrographs: An incorporation of deep learning with a traditional learning approach.

Lymphomas, or cancers of the lymphatic system, account for around half of all blood cancers diagnose...

Non-Invasive Measurement Using Deep Learning Algorithm Based on Multi-Source Features Fusion to Predict PD-L1 Expression and Survival in NSCLC.

BACKGROUND: Programmed death-ligand 1 (PD-L1) assessment of lung cancer in immunohistochemical assay...

Effectiveness of Artificial Intelligence for Personalized Medicine in Neoplasms: A Systematic Review.

PURPOSE: Artificial intelligence (AI) techniques are used in precision medicine to explore novel gen...

Single utility port approach in robot-assisted sleeve segmentectomy for bronchial carcinoid tumor.

Bronchial carcinoid tumors are low-grade malignant and lung-sparing surgery is preferred for the rem...

Testing the reproducibility and robustness of the cancer biology literature by robot.

Scientific results should not just be 'repeatable' (replicable in the same laboratory under identica...

Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis.

OBJECTIVES: To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy ...

Clinicians' Attitudes and Behaviors Towards Communicating Electronically with Patients: A Grounded Practical Theory Approach.

Secure messaging (SM), asynchronous communication between patients and clinicians, is an increasingl...

Research Highlight: Use of Generative Images Created with Artificial Intelligence for Brain Tumor Imaging.

Bayesian networks elucidate complex genomic landscapes in cancer.

Bayesian networks (BNs) are disciplined, explainable Artificial Intelligence models that can describ...

Robot-assisted radical prostatectomy in the treatment of patients with clinically high-risk localized and locally advanced prostate cancer: single surgeons functional and oncologic outcomes.

BACKGROUND: Optimal treatment approaches for high-risk localized and locally advanced prostate cance...

Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram.

OBJECTIVES: To implement a pipeline to automatically segment the ROI and to use a nomogram integrati...

Deep Learning-Based Model for Identifying Tumors in Endoscopic Images From Patients With Locally Advanced Rectal Cancer Treated With Total Neoadjuvant Therapy.

BACKGROUND: A barrier to the widespread adoption of watch-and-wait management for locally advanced r...

Protection against ulcerative colitis and colorectal cancer by evodiamine via anti‑inflammatory effects.

Evodiamine (Evo) is an alkaloid that can be extracted from the berry fruit and has been reported to...

A deep learning model (FociRad) for automated detection of γ-H2AX foci and radiation dose estimation.

DNA double-strand breaks (DSBs) are the most lethal form of damage to cells from irradiation. γ-H2AX...

A two-stage deep learning architecture for radiographic staging of periodontal bone loss.

BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis ...

Prior information-based high-resolution tomography image reconstruction from a single digitally reconstructed radiograph.

Tomography images are essential for clinical diagnosis and trauma surgery, allowing doctors to under...

Predicting the Survival of Cancer Patients With Multimodal Graph Neural Network.

In recent years, cancer patients survival prediction holds important significance for worldwide heal...

Multi-Modal Classification for Human Breast Cancer Prognosis Prediction: Proposal of Deep-Learning Based Stacked Ensemble Model.

Breast Cancer is a highly aggressive type of cancer generally formed in the cells of the breast. Des...

Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.

PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using P...