AI Medical Compendium Topic:
Clinical Decision-Making

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Characterization of Change and Significance for Clinical Findings in Radiology Reports Through Natural Language Processing.

Journal of digital imaging
We built a natural language processing (NLP) method to automatically extract clinical findings in radiology reports and characterize their level of change and significance according to a radiology-specific information model. We utilized a combination...

Deep Diabetologist: Learning to Prescribe Hypoglycemic Medications with Recurrent Neural Networks.

Studies in health technology and informatics
In healthcare, applying deep learning models to electronic health records (EHRs) has drawn considerable attention. This sequential nature of EHR data make them wellmatched for the power of Recurrent Neural Network (RNN). In this poster, we propose "D...

Avoiding Overfitting in Deep Neural Networks for Clinical Opinions Generation from General Blood Test Results.

Studies in health technology and informatics
We have used deep neural networks (DNNs) to generate clinical opinions from general blood test results. DNNs have overfitting problem in general. We believe the complex structure of DNN and insufficient data to be the major reasons of overfitting in ...

Big Data and Machine Learning in Plastic Surgery: A New Frontier in Surgical Innovation.

Plastic and reconstructive surgery
Medical decision-making is increasingly based on quantifiable data. From the moment patients come into contact with the health care system, their entire medical history is recorded electronically. Whether a patient is in the operating room or on the ...

Detecting Learning and Reasoning Patterns in a CDSS for Dementia Investigation.

Studies in health technology and informatics
Reasoning conducted in clinical practice is manifested through different and often combined reasoning and learning strategies, adjusted to the characteristics of the available information, the medical professional's experience and skills, and the ava...

Using EHRs for Heart Failure Therapy Recommendation Using Multidimensional Patient Similarity Analytics.

Studies in health technology and informatics
Electronic Health Records (EHRs) contain a wealth of information about an individual patient's diagnosis, treatment and health outcomes. This information can be leveraged effectively to identify patients who are similar to each for disease diagnosis ...