AIMC Topic: Humans

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The practical implementation of artificial intelligence technologies in medicine.

Nature medicine
The development of artificial intelligence (AI)-based technologies in medicine is advancing rapidly, but real-world clinical implementation has not yet become a reality. Here we review some of the key practical issues surrounding the implementation o...

A guide to deep learning in healthcare.

Nature medicine
Here we present deep-learning techniques for healthcare, centering our discussion on deep learning in computer vision, natural language processing, reinforcement learning, and generalized methods. We describe how these computational techniques can im...

Identifying facial phenotypes of genetic disorders using deep learning.

Nature medicine
Syndromic genetic conditions, in aggregate, affect 8% of the population. Many syndromes have recognizable facial features that are highly informative to clinical geneticists. Recent studies show that facial analysis technologies measured up to the ca...

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.

Nature medicine
Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG workflow. Widely available digital ECG data and the algorithmic paradigm of deep learning present an opportunity to substantially improve the accuracy and s...

Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram.

Nature medicine
Asymptomatic left ventricular dysfunction (ALVD) is present in 3-6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found. An inexpensive, noninvasive screening tool for ALVD in the doctor's ...

Robot-assisted laparoscopic vs laparoscopic donor nephrectomy in renal transplantation: A meta-analysis.

Clinical transplantation
BACKGROUND: Currently, the robot-assisted laparoscopic donor nephrectomy (RDN) technique is used for live donor nephrectomy. Does it provide sufficient safety and benefits for living donors? We conducted a meta-analysis to assess the safety and effic...

Artificial intelligence for the real-time classification of intrapapillary capillary loop patterns in the endoscopic diagnosis of early oesophageal squamous cell carcinoma: A proof-of-concept study.

United European gastroenterology journal
BACKGROUND: Intrapapillary capillary loops (IPCLs) represent an endoscopically visible feature of early squamous cell neoplasia (ESCN) which correlate with invasion depth - an important factor in the success of curative endoscopic therapy. IPCLs visu...

Classification of gait patterns between patients with Parkinson's disease and healthy controls using phase space reconstruction (PSR), empirical mode decomposition (EMD) and neural networks.

Neural networks : the official journal of the International Neural Network Society
Parkinson's disease (PD) is a common neurodegenerative disorder that affects human's quality of life, especially leading to locomotor deficits such as postural instability and gait disturbances. Gait signal is one of the best features to characterize...

A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery.

Journal of medical systems
Robot-assisted surgery (RAS) requires a large capital investment by healthcare organizations. The cost of a robotic unit is fixed, so institutions must maximize use of each unit by utilizing all available operating room block time. One way to increas...

An Enhancement of Computer Aided Approach for Colon Cancer Detection in WCE Images Using ROI Based Color Histogram and SVM2.

Journal of medical systems
The colon cancer is formed by uncontrollable growth of abnormal cells in large intestine or colon that can affect both men and women and it is third cancer disease in the world. At present, Wireless Capsule Endoscopy (WCE) screening method is utilize...