AIMC Topic: Humans

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Technological advances for the detection of melanoma: Advances in diagnostic techniques.

Journal of the American Academy of Dermatology
Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patien...

The impact of deep convolutional neural network-based artificial intelligence on colonoscopy outcomes: A systematic review with meta-analysis.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: The utility of artificial intelligence (AI) in colonoscopy has gained popularity in current times. Recent trials have evaluated the efficacy of deep convolutional neural network (DCNN)-based AI system in colonoscopy for improving ...

Deep learning for the determination of myometrial invasion depth and automatic lesion identification in endometrial cancer MR imaging: a preliminary study in a single institution.

European radiology
OBJECTIVE: To determine the diagnostic performance of a deep learning (DL) model in evaluating myometrial invasion (MI) depth on T2-weighted imaging (T2WI)-based endometrial cancer (EC) MR imaging (ECM).

Predicting severe clinical events by learning about life-saving actions and outcomes using distant supervision.

Journal of biomedical informatics
Medical error is a leading cause of patient death in the United States. Among the different types of medical errors, harm to patients caused by doctors missing early signs of deterioration is especially challenging to address due to the heterogeneity...

A convolutional neural network to detect scoliosis treatment in radiographs.

International journal of computer assisted radiology and surgery
PURPOSE: The aim of this work is to propose a classification algorithm to automatically detect treatment for scoliosis (brace, implant or no treatment) in postero-anterior radiographs. Such automatic labelling of radiographs could represent a step to...

Optimized Multimetal Sensitized Phosphor for Enhanced Red Up-Conversion Luminescence by Machine Learning.

ACS combinatorial science
In this research, machine learning including the genetic algorithm (GA) and support vector machine (SVM) algorithm is used to solve the "low up-conversion luminescence (UCL) intensity" problem in order to find the optimal phosphor with enhanced red U...

Between Web search engines and artificial intelligence: what side is shown in laboratory tests?

Diagnosis (Berlin, Germany)
BACKGROUND: The number of websites providing laboratory test information is increasing fast, although the accuracy of reported resources is sometimes questionable. The aim of this study was to assess the quality of online retrievable information by G...

Early experience with Watson for Oncology: a clinical decision-support system for prostate cancer treatment recommendations.

World journal of urology
PURPOSE: Urological oncologists have difficulty providing optimal personalized care due to rapid alterations in scientific research results, medical advancements, and treatment guidelines. IBM's Watson for Oncology (WFO) is an artificial intelligence...

Using Deep Learning to Automate Goldmann Applanation Tonometry Readings.

Ophthalmology
PURPOSE: To develop an objective and automated method for measuring intraocular pressure using deep learning and fixed-force Goldmann applanation tonometry (GAT) techniques.

Proceedings from the First Global Artificial Intelligence in Gastroenterology and Endoscopy Summit.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Artificial intelligence (AI), specifically deep learning, offers the potential to enhance the field of GI endoscopy in areas ranging from lesion detection and classification to quality metrics and documentation. Progress in this ...