AIMC Topic: Machine Learning

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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.

PloS one
Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-being of patients and develop customized therapeutic plans. Despite its importance, achieving precise forecasts remains a formidable challenge. To tackle...

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

PloS one
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...

Statistical and machine learning models for predicting university dropout and scholarship impact.

PloS one
Although student dropout is an inevitable aspect of university enrollment, when analyzed, universities can gather information which enables them to take preventative actions that mitigate dropout risk. We study a data set consisting of 4,424 records ...

Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.

PloS one
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...

The impact and return-on-investment of evidence-based practice in conservation and environmental management: A machine learning-assisted scoping review protocol.

PloS one
Evidence-based Practice (EBP) is a vital principle, with its origins in the 1970s, that has transformed the disciplines of medicine and healthcare. The use of best available evidence to inform decisions and best practice has since spread across other...

Application of IRSA-BP neural network in diagnosing diabetes.

PloS one
Within the healthcare sector, the application of machine learning is gaining prominence, notably enhancing the efficiency and precision of diagnostic procedures. This study focuses on this key area of diabetes prediction and aims to develop an innova...

Online continuous learning of users suicidal risk on social media.

Artificial intelligence in medicine
Suicide is a tragedy for family and society. With social media becoming an integral part of people's life nowadays, assessing suicidal risk based on one's social media behavior has drawn increasing research attentions. The majority of the works train...

Construction of a novel online calculator for prediction of osteoporosis risk in Chinese type 2 diabetes patients.

Experimental gerontology
BACKGROUND: Type 2 diabetes (T2D) has been established as an independent risk factor for osteoporosis, often resulting in a poor prognosis. Thus, it is crucial for clinicians to diagnose osteoporosis in diabetic patients. This study aimed to develop ...

Disrupted functional topology of the white matter connectome in rhegmatogenous retinal detachment: insights from graph theory and machine learning.

Neuroreport
BACKGROUND: Rhegmatogenous retinal detachment (RRD) is known to induce functional alterations in the gray matter regions associated with vision. However, the impact of RRD on the white matter (WM) connectome remains largely unexplored.

Modeling Soil pH at regional scale using environmental covariates and machine learning algorithm.

Environmental monitoring and assessment
Soil pH serves as a critical indicator of soil chemistry and fertility, and mapping its spatial distribution holds significant importance for effective crop management. Digital soil mapping (DSM) is a commonly employed method for making rapid and cos...