AIMC Topic: Models, Statistical

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A systematic comparison of generative models for medical images.

International journal of computer assisted radiology and surgery
PURPOSE: This work aims for a systematic comparison of popular shape and appearance models. Here, two statistical and four deep-learning-based shape and appearance models are compared and evaluated in terms of their expressiveness described by their ...

Incomplete Label Multiple Instance Multiple Label Learning.

IEEE transactions on pattern analysis and machine intelligence
With increasing data volumes, the bottleneck in obtaining data for training a given learning task is the cost of manually labeling instances within the data. To alleviate this issue, various reduced label settings have been considered including semi-...

Developing machine learning models for prediction of mortality in the medical intensive care unit.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alert of patient deterioration is essential for prompt medical intervention in the Medical Intensive Care Unit (MICU). Logistic Regression (LR) has been used for the development of most conventional severity-of-illness scori...

PCA driven mixed filter pruning for efficient convNets.

PloS one
Deployment of the deep neural networks (DNNs) on resource-constrained devices is a challenging task due to their limited memory and computational power. In most cases, the pruning techniques do not prune the DNNs to full extent and redundancy still e...

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Scientific reports
Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity. Interventions initiated early in pregnancy can reduce the rate of GDM i...

Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches.

PloS one
The COVID-19 pandemic has been widely spread and affected millions of people and caused hundreds of deaths worldwide, especially in patients with comorbilities and COVID-19. This manuscript aims to present models to predict, firstly, the number of co...

Probabilistic Model-Based Learning Control of a Soft Pneumatic Glove for Hand Rehabilitation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Stroke survivors are usually unable to perform activities of daily living (ADL) independently due to loss of hand functions. Soft pneumatic gloves provide a promising assistance approach for stroke survivors to conduct ADL tasks. However, ...

Machine learning prediction model of acute kidney injury after percutaneous coronary intervention.

Scientific reports
Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditional risk model provided by the National Cardiovascular Data Registry (NCDR) is useful for predictin...

Multi-Regional Modeling of Cumulative COVID-19 Cases Integrated with Environmental Forest Knowledge Estimation: A Deep Learning Ensemble Approach.

International journal of environmental research and public health
Reliable modeling of novel commutative cases of COVID-19 (CCC) is essential for determining hospitalization needs and providing the benchmark for health-related policies. The current study proposes multi-regional modeling of CCC cases for the first s...

Percolation in networks with local homeostatic plasticity.

Nature communications
Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportati...