AI Medical Compendium Journal:
Frontiers in oncology

Showing 11 to 20 of 74 articles

Intraoperative circulation predict prolonged length of stay after head and neck free flap reconstruction: a retrospective study based on machine learning.

Frontiers in oncology
BACKGROUND: Head and neck free flap reconstruction presents challenges in managing intraoperative circulation, potentially leading to prolonged length of stay (PLOS). Limited research exists on the associations between intraoperative circulation and ...

Postoperative fever after elective minimally invasive resection for gastric and colorectal cancer: incidence, risk factors and characteristics.

Frontiers in oncology
PURPOSE: To analyze the incidence and risk factors of postoperative fever (POF) in gastrointestinal cancer (GIC), discuss the influence of POF on short-term clinical outcomes, and predict anastomotic leakage (AL) based on POF characteristics.

A stacking ensemble system for identifying the presence of histological variants in bladder carcinoma: a multicenter study.

Frontiers in oncology
PURPOSE: To create a system to enable the identification of histological variants of bladder cancer in a simple, efficient, and noninvasive manner.

The accuracy of radiomics in diagnosing tumor deposits and perineural invasion in rectal cancer: a systematic review and meta-analysis.

Frontiers in oncology
BACKGROUND: Radiomics has emerged as a promising approach for diagnosing, treating, and evaluating the prognosis of various diseases in recent years. Some investigators have utilized radiomics to create preoperative diagnostic models for tumor deposi...

Interpretable machine learning models for predicting skip metastasis in cN0 papillary thyroid cancer based on clinicopathological and elastography radiomics features.

Frontiers in oncology
BACKGROUND: Skip lymph node metastasis (SLNM) in papillary thyroid cancer (PTC) involves cancer cells bypassing central nodes to directly metastasize to lateral nodes, often undetected by standard preoperative ultrasonography. Although multiple model...

Comparative study of robotic-assisted vs. laparoscopic surgery for colorectal cancer: a single-center experience.

Frontiers in oncology
BACKGROUND: Colorectal cancer (CRC) surgeries are commonly performed using either robotic-assisted colorectal surgery (RACS) or laparoscopic colorectal surgery (LCS). This study aimed to compare clinical and surgical outcomes between RACS and LCS for...

Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis.

Frontiers in oncology
BACKGROUND: Breast cancer (BC), as a leading cause of cancer mortality in women, demands robust prediction models for early diagnosis and personalized treatment. Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising soluti...

AI predicting recurrence in non-muscle-invasive bladder cancer: systematic review with study strengths and weaknesses.

Frontiers in oncology
BACKGROUND: Non-muscle-invasive Bladder Cancer (NMIBC) is notorious for its high recurrence rate of 70-80%, imposing a significant human burden and making it one of the costliest cancers to manage. Current prediction tools for NMIBC recurrence rely o...

Global research trends in the application of artificial intelligence in oncology care: a bibliometric study.

Frontiers in oncology
OBJECTIVE: To use bibliometric methods to analyze the prospects and development trends of artificial intelligence(AI) in oncology nursing from 1994 to 2024, providing guidance and reference for oncology nursing professionals and researchers.

Machine learning-based identification of proteomic markers in colorectal cancer using UK Biobank data.

Frontiers in oncology
Colorectal cancer is one of the leading causes of cancer-related mortality in the world. Incidence and mortality are predicted to rise globally during the next several decades. When detected early, colorectal cancer is treatable with surgery and medi...