AIMC Topic: Models, Statistical

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An Explainable Artificial Intelligence Predictor for Early Detection of Sepsis.

Critical care medicine
OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...

Synthetic minority oversampling of vital statistics data with generative adversarial networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extrem...

The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Critical care medicine
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...

COVID-19 and the epistemology of epidemiological models at the dawn of AI.

Annals of human biology
The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: 'model organisms' chosen for their phylogenetic/aetiological similarities; multivariable...

Enhancing scientific discoveries in molecular biology with deep generative models.

Molecular systems biology
Generative models provide a well-established statistical framework for evaluating uncertainty and deriving conclusions from large data sets especially in the presence of noise, sparsity, and bias. Initially developed for computer vision and natural l...

Designing an optimal inventory management model for the blood supply chain: Synthesis of reusable simulation and neural network.

Medicine
Blood supply managers in the blood supply chain have always sought to create enough reserves to increase access to different blood products and reduce the mortality rate resulting from expired blood. Managers' adequate and timely response to their cu...

Novel Feature Selection for Artificial Intelligence Using Item Response Theory for Mortality Prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Feature selection is a critical component in supervised machine learning classification analyses. Extraneous features introduce noise and inefficiencies into the system leading to a need for feature reduction techniques. Many feature reduction models...

Similar Disease Prediction With Heterogeneous Disease Information Networks.

IEEE transactions on nanobioscience
Studying the similarity of diseases can help us to explore the pathological characteristics of complex diseases, and help provide reliable reference information for inferring the relationship between new diseases and known diseases, so as to develop ...

A New Classification of Benign, Premalignant, and Malignant Endometrial Tissues Using Machine Learning Applied to 1413 Candidate Variables.

International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists
Benign normal (NL), premalignant (endometrial intraepithelial neoplasia, EIN) and malignant (cancer, EMCA) endometria must be precisely distinguished for optimal management. EIN was objectively defined previously as a regression model incorporating m...

Evaluation of Document Retrieval Systems on a Medical Corpus in French: Indexation vs. Feature Learning.

Studies in health technology and informatics
This paper presents five document retrieval systems for a small (few thousands) and domain specific corpora (weekly peer-reviewed medical journals published in French) as well as an evaluation methodology to quantify the models performance. The propo...