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Pancreatic Neoplasms

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Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear. Aim of the study was to assess the efficacy of repeat celiac plexus neurolysis and to build an artificial neural network model able to predict pain ...

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

IEEE transactions on medical imaging
We aim at segmenting a wide variety of organs, including tiny targets (e.g., adrenal gland), and neoplasms (e.g., pancreatic cyst), from abdominal CT scans. This is a challenging task in two aspects. First, some organs (e.g., the pancreas), are highl...

Clinically Applicable Deep Learning Algorithm Using Quantitative Proteomic Data.

Journal of proteome research
Deep learning (DL), a type of machine learning approach, is a powerful tool for analyzing large sets of data that are derived from biomedical sciences. However, it remains unknown whether DL is suitable for identifying contributing factors, such as b...

Markerless Pancreatic Tumor Target Localization Enabled By Deep Learning.

International journal of radiation oncology, biology, physics
PURPOSE: Deep learning is an emerging technique that allows us to capture imaging information beyond the visually recognizable level of a human being. Because of the anatomic characteristics and location, on-board target verification for radiation de...

Diagnostic ability of artificial intelligence using deep learning analysis of cyst fluid in differentiating malignant from benign pancreatic cystic lesions.

Scientific reports
The diagnosis of pancreatic cystic lesions remains challenging. This study aimed to investigate the diagnostic ability of carcinoembryonic antigen (CEA), cytology, and artificial intelligence (AI) by deep learning using cyst fluid in differentiating ...

Pixel-to-Pixel Learning With Weak Supervision for Single-Stage Nucleus Recognition in Ki67 Images.

IEEE transactions on bio-medical engineering
OBJECTIVE: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 immunohistochemistry stained images. Although many automated methods have been proposed, most use a multi-stage processing pipeli...

Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination.

Biomarkers in medicine
AIM: Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.

Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches.

IEEE transactions on medical imaging
Risk stratification (characterization) of tumors from radiology images can be more accurate and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through such tools can also enable non-invasive cancer staging, prognosis, and fo...

Distal pancreatectomy with en-bloc celiac axis resection (DP-CAR) through retroperitoneal-first laparoscopic approach (Retlap): A novel strategy for achieving accurate evaluation of resectability and minimal invasiveness.

Surgical oncology
BACKGROUND: Distal pancreatectomy with en-bloc celiac axis resection (DP-CAR) for borderline resectable pancreatic body cancer is increasingly being performed [1,2]. For survival benefits, obtaining margin-free resection (R0 resection) is crucial [3]...