AIMC Topic: Prognosis

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Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis.

Schizophrenia research
Recent studies have reported an association between psychopathology and subsequent clinical and functional outcomes in people at ultra-high risk (UHR) for psychosis. This has led to the suggestion that psychopathological information could be used to ...

GC-MS Metabolomics Identifies Metabolite Alterations That Precede Subclinical Mastitis in the Blood of Transition Dairy Cows.

Journal of proteome research
The objectives of this study were to determine alterations in the serum metabolites related to amino acid (AA), carbohydrate, and lipid metabolism in transition dairy cows before diagnosis of subclinical mastitis (SCM), during, and after diagnosis of...

Predictors of in-hospital mortality following major lower extremity amputations in type 2 diabetic patients using artificial neural networks.

BMC medical research methodology
BACKGROUND: Outcome prediction is important in the clinical decision-making process. Artificial neural networks (ANN) have been used to predict the risk of post-operative events, including survival, and are increasingly being used in complex medical ...

An intelligent prognostic system for analyzing patients with paraquat poisoning using arterial blood gas indexes.

Journal of pharmacological and toxicological methods
The arterial blood gas (ABG) test is used to assess gas exchange in the lung, and the acid-base level in the blood. However, it is still unclear whether or not ABG test indexes correlate with paraquat (PQ) poisoning. This study investigates the predi...

Transcriptome assists prognosis of disease severity in respiratory syncytial virus infected infants.

Scientific reports
Respiratory syncytial virus (RSV) causes infections that range from common cold to severe lower respiratory tract infection requiring high-level medical care. Prediction of the course of disease in individual patients remains challenging at the first...

A Novel and Effective Method for Congestive Heart Failure Detection and Quantification Using Dynamic Heart Rate Variability Measurement.

PloS one
Risk assessment of congestive heart failure (CHF) is essential for detection, especially helping patients make informed decisions about medications, devices, transplantation, and end-of-life care. The majority of studies have focused on disease detec...

Advanced literature analysis in a Big Data world.

Annals of the New York Academy of Sciences
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological ...

Early Detection of Heart Failure Using Electronic Health Records: Practical Implications for Time Before Diagnosis, Data Diversity, Data Quantity, and Data Density.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Using electronic health records data to predict events and onset of diseases is increasingly common. Relatively little is known, although, about the tradeoffs between data requirements and model utility.

Adequate tacrolimus concentration for myasthenia gravis treatment.

European journal of neurology
BACKGROUND AND PURPOSE: A single, oral dose of 3 mg/day tacrolimus, approved for myasthenia gravis (MG) treatment in Japan, was shown to reduce steroid dose and anti-acetylcholine receptor (AChR) antibody titers as well as to improve MG symptoms. How...

An algorithm for direct causal learning of influences on patient outcomes.

Artificial intelligence in medicine
OBJECTIVE: This study aims at developing and introducing a new algorithm, called direct causal learner (DCL), for learning the direct causal influences of a single target. We applied it to both simulated and real clinical and genome wide association ...