AI Medical Compendium Journal:
Anticancer research

Showing 1 to 10 of 28 articles

Machine Learning Model to Guide Empirical Antimicrobial Therapy in Febrile Neutropenic Patients With Hematologic Malignancies.

Anticancer research
BACKGROUND/AIM: Optimal antimicrobial selection for patients with febrile neutropenia (FN) may differ depending on the underlying mechanisms. We aimed to develop a model for predicting the severity of bacteremia in patients with FN and hematologic ma...

Four Different Artificial Intelligence Models Logistic Regression to Enhance the Diagnostic Accuracy of Fecal Immunochemical Test in the Detection of Colorectal Carcinoma in a Screening Setting.

Anticancer research
BACKGROUND/AIM: This study aimed to evaluate the diagnostic accuracy (DA) of four artificial intelligence (AI) models compared to logistic regression (LR) in enhancing the performance of the fecal immunochemical test (FIT) for the detection of colore...

Light Bladder Net: Non-invasive Bladder Cancer Prediction by Weighted Deep Learning Approaches and Graphical Data Transformation.

Anticancer research
BACKGROUND/AIM: Bladder cancer (BCa) is associated with high recurrence rates, emphasizing the importance of early and accurate detection. This study aimed to develop a lightweight and fast deep learning model, Light-Bladder-Net (LBN), for non-invasi...

The Impact of AI-driven Remote Patient Monitoring on Cancer Care: A Systematic Review.

Anticancer research
The coronavirus disease 2019 (COVID-19) pandemic necessitated a shift in healthcare delivery, emphasizing the need for remote patient monitoring (RPM) to minimize infection risks. This review aimed to evaluate the applications of artificial intellige...

Artificial Intelligence Models Could Enhance the Diagnostic Accuracy (DA) of Fecal Immunochemical Test (FIT) in the Detection of Colorectal Adenoma in a Screening Setting.

Anticancer research
BACKGROUND/AIM: This study evaluated the diagnostic accuracy (DA) for colorectal adenomas (CRA), screened by fecal immunochemical test (FIT), using five artificial intelligence (AI) models: logistic regression (LR), support vector machine (SVM), neur...

A Machine Learning Model to Predict the Histology of Retroperitoneal Lymph Node Dissection Specimens.

Anticancer research
BACKGROUND/AIM: While post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) benefits patients with teratoma or viable germ cell tumors (GCT), it becomes overtreatment if necrosis is detected in PC-RPLND specimens. Serum microRNA-371a-3p ...

Association Between Acute Kidney Injury and the Trendelenburg Position Angle During Robot-assisted Radical Prostatectomy.

Anticancer research
BACKGROUND/AIM: Robot-assisted radical prostatectomy (RARP) has been widely adopted as the standard treatment for localized prostate cancer. RARP is safer and results in better oncological control than conventional open total prostatectomy. However, ...

AI-based Apoptosis Cell Classification Using Phase-contrast Images of K562 Cells.

Anticancer research
BACKGROUND/AIM: This study aimed to automate the classification of cells, particularly in identifying apoptosis, using artificial intelligence (AI) in conjunction with phase-contrast microscopy. The objective was to reduce reliance on manual observat...

Proctoring System Enables Safe Induction of Robotic Gastrectomy: Short-term Outcomes of the First 10 Cases.

Anticancer research
BACKGROUND/AIM: The Japan Society of Endoscopic Surgery (JSES) proctoring system was established to prevent serious pancreatic pressure injuries in Japan in 2019. To safely perform robotic gastrectomy (RG) in our hospital, which has no experience in ...