AI Medical Compendium Topic

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Diagnosis

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Trust in artificial intelligence for medical diagnoses.

Progress in brain research
We present two online experiments investigating trust in artificial intelligence (AI) as a primary and secondary medical diagnosis tool and one experiment testing two methods to increase trust in AI. Participants in Experiment 1 read hypothetical sce...

A Perspective from a Case Conference on Comparing the Diagnostic Process: Human Diagnostic Thinking vs. Artificial Intelligence (AI) Decision Support Tools.

International journal of environmental research and public health
Artificial intelligence (AI) has made great contributions to the healthcare industry. However, its effect on medical diagnosis has not been well explored. Here, we examined a trial comparing the thinking process between a computer and a master in dia...

Improving the accuracy of medical diagnosis with causal machine learning.

Nature communications
Machine learning promises to revolutionize clinical decision making and diagnosis. In medical diagnosis a doctor aims to explain a patient's symptoms by determining the diseases causing them. However, existing machine learning approaches to diagnosis...

Closing the translation gap: AI applications in digital pathology.

Biochimica et biophysica acta. Reviews on cancer
Recent advances in artificial intelligence show tremendous promise to improve the accuracy, reproducibility, and availability of medical diagnostics across a number of medical subspecialities. This is especially true in the field of digital pathology...

Generative transfer learning for measuring plausibility of EHR diagnosis records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Due to a complex set of processes involved with the recording of health information in the Electronic Health Records (EHRs), the truthfulness of EHR diagnosis records is questionable. We present a computational approach to estimate the pro...

One-dimensional convolutional neural network-based active feature extraction for fault detection and diagnosis of industrial processes and its understanding via visualization.

ISA transactions
Feature extraction from process signals enables process monitoring models to be effective in industrial processes. Deep learning presents extensive possibilities for extracting abstract features from image and visual data. However, the main inputs of...