AIMC Topic: Machine Learning

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A Comparison of Models Predicting One-Year Mortality at Time of Admission.

Journal of pain and symptom management
CONTEXT: Hospitalization provides an opportunity to address end-of-life care (EoLC) preferences if patients at risk of death can be accurately identified while in the hospital. The modified Hospital One-Year Mortality Risk (mHOMR) uses demographic an...

Domain- and task-specific transfer learning for medical segmentation tasks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Transfer learning is a valuable approach to perform medical image segmentation in settings with limited cases available for training convolutional neural networks (CNN). Both the source task and the source domain influence ...

A hybridization of distributed policy and heuristic augmentation for improving federated learning approach.

Neural networks : the official journal of the International Neural Network Society
Modifying the existing models of classifiers' operation is primarily aimed at increasing the effectiveness as well as minimizing the training time. An additional advantage is the ability to quickly implement a given solution to the real needs of the ...

Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review.

The Lancet. Digital health
Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key u...

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Journal of biomedical informatics
BACKGROUND: Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created ad-hoc using a few manually selected variables based on c...

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions.

Sensors (Basel, Switzerland)
The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medic...

Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study.

Sensors (Basel, Switzerland)
Recent developments in cloud computing and the Internet of Things have enabled smart environments, in terms of both monitoring and actuation. Unfortunately, this often results in unsustainable cloud-based solutions, whereby, in the interest of simpli...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Journal of healthcare engineering
Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was studied. In this study, 74 surgically treated gynecologic tumor patients were randomly selected from...

Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge.

PloS one
BACKGROUND: Delays in patient flow and a shortage of hospital beds are commonplace in hospitals during periods of increased infection incidence, such as seasonal influenza and the COVID-19 pandemic. The objective of this study was to develop and eval...

A hybrid machine-learning model to map glacier-related debris flow susceptibility along Gyirong Zangbo watershed under the changing climate.

The Science of the total environment
Gyirong serves as an important channel to Chine-Nepal Economic Corridor, which is also the only land route for China-Nepal trade since the 2015 earthquake. However, the Gyirong corridor suffers from glacier-related debris flow from every April to Sep...