AIMC Topic: Cause of Death

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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study.

Journal of forensic and legal medicine
OBJECTIVES: Automatic text classification techniques are useful for classifying plaintext medical documents. This study aims to automatically predict the cause of death from free text forensic autopsy reports by comparing various schemes for feature ...

Application of artificial neural network in medical geochemistry.

Environmental geochemistry and health
For the evaluation of various adverse health effects of chemical elements occurring in the environment on humans, the comparison and linking of geochemical data (chemical composition of groundwater, soils, and dusts) with data on health status of pop...

Aging, frailty and complex networks.

Biogerontology
When people age their mortality rate increases exponentially, following Gompertz's law. Even so, individuals do not die from old age. Instead, they accumulate age-related illnesses and conditions and so become increasingly vulnerable to death from va...

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

PloS one
OBJECTIVES: Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-bas...

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...

Racial/Ethnic Disparities in Rates of Traumatic Injury in Arizona, 2011-2012.

Public health reports (Washington, D.C. : 1974)
OBJECTIVE: The purpose of this study was to compare the rates of traumatic injury among five racial/ethnic groups in Arizona and to identify which mechanisms and intents of traumatic injury were predominant in each group.

Automatic ICD-10 classification of cancers from free-text death certificates.

International journal of medical informatics
OBJECTIVE: Death certificates provide an invaluable source for cancer mortality statistics; however, this value can only be realised if accurate, quantitative data can be extracted from certificates--an aim hampered by both the volume and variable na...

Validating estimates of prevalence of non-communicable diseases based on household surveys: the symptomatic diagnosis study.

BMC medicine
BACKGROUND: Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing me...

Adaptive modelling approach for predicting causes of death: insights from verbal autopsy data in Tanzania.

International health
BACKGROUND: The World Health Organization (WHO) has approved the use of a verbal autopsy (VA), a survey-based approach to generate out-of-hospital causes of death (CoDs). Through this study, an adaptive Bayesian networks machine learning model was de...

Sex-specific prognostic value of automated epicardial adipose tissue quantification on serial lung cancer screening chest computed tomography.

European heart journal. Cardiovascular Imaging
AIMS: Epicardial adipose tissue (EAT) is a metabolically active fat depot associated with coronary atherosclerosis and cardiovascular (CV) risk. While EAT is a known prognostic marker in lung cancer screening, its sex-specific prognostic value remain...