AIMC Topic: Humans

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Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets.

PloS one
OBJECTIVES: The objective of this study was to develop and validate a state-of-the-art, deep learning (DL)-based model for detecting breast cancers on mammography.

Reduction of multiple-caregiver assistance through the long-term use of a transfer support robot in a nursing facility.

Assistive technology : the official journal of RESNA
The long-term use of transfer support robots in nursing facilities is an important option for improving the efficiency of care work. The "Resyone" transfer support robot is a combination of an electric care bed and a wheelchair, and the wheelchair ha...

Minimally Invasive Esophagectomy Is Associated with Superior Survival Compared to Open Surgery.

The American surgeon
INTRODUCTION: Minimally invasive esophagectomy (MIE) has not been associated with a long-term survival advantage compared to open esophagectomy (OE). We investigated survival differences between MIE, including laparoscopic and robotic, and OE.

The past, the present and the future of machine learning and artificial intelligence in anesthesia and Postanesthesia Care Units (PACU).

Minerva anestesiologica
Over the past decade, artificial intelligence (AI) has largely penetrated our daily life. Hence, our expectations regarding clinical AI are very high. However, in healthcare and especially in perioperative medicine, the impact of AI is still relative...

A fully automated sex estimation for proximal femur X-ray images through deep learning detection and classification.

Legal medicine (Tokyo, Japan)
PURPOSE: To develop a fully automated deep learning pipeline using digital radiographs to detect the proximal femur region for accurate automated sex estimation.

MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Rapid advancements in deep learning have led to many recent breakthroughs. While deep learning models achieve superior performance, often statistically better than humans, their adoption into safety-critical settings, such as healthcare or self-drivi...

Concurrent robot-assisted radical prostatectomy and robot-assisted partial nephrectomy for patients with synchronous prostate cancer and small renal tumor: A case series of five patients.

Asian journal of endoscopic surgery
Robotic surgery has become widely used in the field of urology. We experienced concurrent robot-assisted radical prostatectomy (RARP) and robot-assisted partial nephrectomy (RAPN) for the complex cases of synchronous primary cancers. Concurrent RARP ...

Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prostate cancer is the most common cancer of the male reproductive system. With the development of medical imaging technology, magnetic resonance images (MRI) have been used in the diagnosis and treatment of prostate cancer ...

A visually interpretable detection method combines 3-D ECG with a multi-VGG neural network for myocardial infarction identification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic recognition of myocardial infarction (MI) by artificial intelligence (AI) has been an emerging topic of academic research and an existing classification method that can recognize conventional electrocardiogram ...

Improving convolutional neural network learning based on a hierarchical bezier generative model for stenosis detection in X-ray images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic detection of stenosis on X-ray Coronary Angiography (XCA) images may help diagnose early coronary artery disease. Stenosis is manifested by a buildup of plaque in the arteries, decreasing the blood flow to the hear...