AIMC Topic: Pancreatic Neoplasms

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Assessing the value of deep neural networks for postoperative complication prediction in pancreaticoduodenectomy patients.

PloS one
INTRODUCTION: Pancreaticoduodenectomy (PD) for patients with pancreatic ductal adenocarcinoma (PDAC) is associated with a high risk of postoperative complications (PoCs) and risk prediction of these is therefore critical for optimal treatment plannin...

Assessing Large Language Models for Oncology Data Inference From Radiology Reports.

JCO clinical cancer informatics
PURPOSE: We examined the effectiveness of proprietary and open large language models (LLMs) in detecting disease presence, location, and treatment response in pancreatic cancer from radiology reports.

Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramount importance, given its high mortality rate. Current PDAC risk prediction models rely on a limited number of variables, do not include genetics, and h...

ChatGPT vs. surgeons on pancreatic cancer queries: accuracy & empathy evaluated by patients and experts.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Artificial intelligence (AI) offers potential support in patient-clinician interactions, but its impact on such communication remains unexplored.

Computed tomography-based fully automated artificial intelligence model to predict extrapancreatic perineural invasion in pancreatic ductal adenocarcinoma.

International journal of surgery (London, England)
BACKGROUND: Extrapancreatic perineural invasion (EPNI) increases the risk of postoperative recurrence in pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop and validate a computed tomography (CT)-based, fully automated preoperative ...

Antigen-independent single-cell circulating tumor cell detection using deep-learning-assisted biolasers.

Biosensors & bioelectronics
Circulating tumor cells (CTCs) in the bloodstream are important biomarkers for clinical prognosis of cancers. Current CTC identification methods are based on immuno-labeling, which depends on the differential expression of specific antigens between t...

Advancing frontline early pancreatic cancer detection using within-class feature extraction in FTIR spectroscopy.

Scientific reports
This study introduces a novel approach for the early detection of pancreatic cancer through biofluid spectroscopy, leveraging a unique machine learning pipeline comprising class-specific principal component analysis (PCA), linear discriminant analysi...

Prediction of 12-month recurrence of pancreatic cancer using machine learning and prognostic factors.

BMC medical informatics and decision making
BACKGROUND AND AIM: Pancreatic cancer is lethal and prevalent among other cancer types. The recurrence of this tumor is high, especially in patients who did not receive adjuvant therapies. Early prediction of PC recurrence has a significant role in e...

Enhancing detection of various pancreatic lesions on endoscopic ultrasound through artificial intelligence: a basis for computer-aided detection systems.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Endoscopic ultrasound (EUS) is the most sensitive method for evaluation of pancreatic lesions but is limited by significant operator dependency. Artificial intelligence (AI), in the form of computer-aided detection (CADe) systems,...