BACKGROUND: Endometrial cancer is one of the most common tumors of the female reproductive system and ranks third in the world list of gynecological malignancies that cause death. However, due to the privacy and complexity of pathology images, it is ...
BACKGROUND: Accurate detection of bladder lesions during cystoscopy is crucial for early tumor diagnosis and recurrence monitoring. However, conventional visual inspection methods have low and inconsistent detection rates. This study aimed to evaluat...
BACKGROUND: Postdischarge venous thromboembolism (pdVTE) is a life-threatening complication following resection for pancreatic cancer (PC). While national guidelines recommend extended chemoprophylaxis for all, adherence is low and ranges from 1.5 to...
BACKGROUND: Length of stay (LOS) is a key indicator of posthepatectomy care quality. While clinical factors influencing LOS are identified, the balance between clinical and nonclinical influences remains unquantified. We developed an artificial intel...
BACKGROUND: This study aimed to develop a dynamic survival prediction model utilizing conditional survival (CS) analysis and machine learning techniques for gastric neuroendocrine carcinomas (GNECs).
BACKGROUND: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection afte...
BACKGROUND: Patients with gastric cancer (GC) who experience early recurrence (ER) within 2 years postoperatively have poor prognoses. This study aimed to analyze and predict ER after curative surgery for patients with GC using machine learning (ML) ...
This letter responds to Matsubara's discussion on preserving personal tone in the age of artificial-intelligence-assisted writing. Assistive tools such as large language models (LLMs) can be helpful for busy authors and those who struggle with the En...
MAIN OBJECTIVES: We aimed at comparing intratumoral and peritumoral deep learning, radiomics, and fusion models in predicting KRAS mutations in rectal cancer using endorectal ultrasound imaging.
This article discusses the limitations of artificial intelligence (AI) content detectors, citing studies by Flitcroft et al. The author shares personal experiences in which AI detectors incorrectly flagged human-written content, emphasizing that the ...