AIMC Topic: Logistic Models

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Calibrating random forests for probability estimation.

Statistics in medicine
Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for updating ran...

Identifying Individual-Cancer-Related Genes by Rebalancing the Training Samples.

IEEE transactions on nanobioscience
The identification of individual-cancer-related genes typically is an imbalanced classification issue. The number of known cancer-related genes is far less than the number of all unknown genes, which makes it very hard to detect novel predictions fro...

Diabetic peripheral neuropathy class prediction by multicategory support vector machine model: a cross-sectional study.

Epidemiology and health
OBJECTIVES: Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation. This study used a multicategory su...

Serum 25-hydroxyvitamin D and metabolic syndrome in a Japanese working population: The Furukawa Nutrition and Health Study.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: Increasing evidence has suggested a protective role of vitamin D on metabolic syndrome (MetS). However, studies addressing this issue are limited in Asia and it remains unclear whether calcium could modify the association. We examined the ...

Investigating driver injury severity patterns in rollover crashes using support vector machine models.

Accident; analysis and prevention
Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector ...

A method for modeling co-occurrence propensity of clinical codes with application to ICD-10-PCS auto-coding.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely re...

Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
OBJECTIVES: Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns wit...

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PloS one
BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took acco...

Rapid identification of slow healing wounds.

Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society
Chronic nonhealing wounds have a prevalence of 2% in the United States, and cost an estimated $50 billion annually. Accurate stratification of wounds for risk of slow healing may help guide treatment and referral decisions. We have applied modern mac...

Diagnosis of Acute Coronary Syndrome with a Support Vector Machine.

Journal of medical systems
Acute coronary syndrome (ACS) is a serious condition arising from an imbalance of supply and demand to meet myocardium's metabolic needs. Patients typically present with retrosternal chest pain radiating to neck and left arm. Electrocardiography (ECG...