AIMC Topic: Retrospective Studies

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Tumor-Infiltrating Lymphocyte Recognition in Primary Melanoma by Deep Learning Convolutional Neural Network.

The American journal of pathology
The presence of tumor-infiltrating lymphocytes (TILs) is associated with a favorable prognosis of primary melanoma (PM). Recently, artificial intelligence (AI)-based approach in digital pathology was proposed for the standardized assessment of TILs o...

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Mineral Density Assessment From Low-Dose Chest Computed Tomography.

Academic radiology
RATIONALE AND OBJECTIVES: To develop an intelligent diagnostic model for osteoporosis screening based on low-dose chest computed tomography (LDCT). The model incorporates automatic deep-learning thoracic vertebrae of cancellous bone (TVCB) segmentati...

Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer.

Journal of medical imaging and radiation oncology
INTRODUCTION: Lymph node (LN) metastases are an important determinant of survival in patients with colon cancer, but remain difficult to accurately diagnose on preoperative imaging. This study aimed to develop and evaluate a deep learning model to pr...

Tele-robotic distal gastrectomy with lymph node dissection on a cadaver.

Asian journal of endoscopic surgery
The purpose of this study is to evaluate the performance of tele-robotic distal gastrectomy (tele-RDG) with lymph node dissection (LND) using a novel Japanese-made surgical robot hinotoriā„¢ (Medicaroid, Kobe, Japan) in a cadaver with a presumptive gas...

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

European journal of nuclear medicine and molecular imaging
PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pu...

Artificial intelligence in clinical decision-making: Rethinking personal moral responsibility.

Bioethics
Artificially intelligent systems (AISs) are being created by software developing companies (SDCs) to influence clinical decision-making. Historically, clinicians have led healthcare decision-making, and the introduction of AISs makes SDCs novel actor...

Clinical Outcomes of Robotic Resection for Perihilar Cholangiocarcinoma: A First, Multicenter, Trans-Atlantic, Expert-Center, Collaborative Study.

Annals of surgical oncology
INTRODUCTION: Perihilar cholangiocarcinoma is a difficult cancer to treat with frequent vascular invasion, local recurrence, and poor survival. Due to the need for biliary anastomosis and potential vascular resection, the standard approach is an open...

Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography.

Journal of Korean medical science
BACKGROUND: To propose a deep learning architecture for automatically detecting the complex structure of the aortic annulus plane using cardiac computed tomography (CT) for transcatheter aortic valve replacement (TAVR).

CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To construct and assess a computed tomography (CT)-based deep learning radiomics nomogram (DLRN) for predicting the pathological grade of bladder cancer (BCa) preoperatively.