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Logistic Models

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Potato Late Blight Outbreak: A Study on Advanced Classification Models Based on Meteorological Data.

Sensors (Basel, Switzerland)
While past research has emphasized the importance of late blight infection detection and classification, anticipating the potato late blight infection is crucial from the economic point of view as it helps to significantly reduce the production cost....

Prediction of undernutrition and identification of its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.

PloS one
BACKGROUND AND OBJECTIVES: Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting ...

Assessment of urban flood susceptibility based on a novel integrated machine learning method.

Environmental monitoring and assessment
Flood susceptibility assessment is the premise and foundation to prevent flood disaster events effectively. To accurately assess urban flood susceptibility (UFS), this study first analyzes the advantages and disadvantages of multi-layer perceptron (M...

Prediction of preterm birth using machine learning: a comprehensive analysis based on large-scale preschool children survey data in Shenzhen of China.

BMC pregnancy and childbirth
BACKGROUND: Preterm birth (PTB) is a significant cause of neonatal mortality and long-term health issues. Accurate prediction and timely prevention of PTB are essential for reducing associated child mortality and morbidity. Traditional predictive met...

The use of cloud based machine learning to predict outcome in intracerebral haemorrhage without explicit programming expertise.

Neurosurgical review
Machine Learning (ML) techniques require novel computer programming skills along with clinical domain knowledge to produce a useful model. We demonstrate the use of a cloud-based ML tool that does not require any programming expertise to develop, val...

Artificial intelligence-based molecular property prediction of photosensitising effects of drugs.

Journal of drug targeting
Drug-induced photosensitivity is a potential adverse event of many drugs and chemicals used across a wide range of specialties in clinical medicine. In the present study, we investigated the feasibility of predicting the photosensitising effects of d...

A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Computers, informatics, nursing : CIN
Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier i...

Prediction model for ocular metastasis of breast cancer: machine learning model development and interpretation study.

BMC cancer
BACKGROUND: Breast cancer (BC) is caused by the uncontrolled proliferation of breast epithelial cells followed by malignant transformation, and it has the highest incidence among female malignant tumors. The metastasis of BC occurs through direct and...

A machine learning approach to quantify effects of geometric design features and traffic control devices on wrong-way driving incidents at partial cloverleaf interchange terminals.

Accident; analysis and prevention
This study addresses the issue of wrong-way driving (WWD) incidents at partial cloverleaf (parclo) interchange terminals in the United States. These incidents are a safety concern, often attributed to geometric design features and inadequate traffic ...

Machine learning insights on activities of daily living disorders in Chinese older adults.

Experimental gerontology
OBJECTIVE: This study on the aged population in China first used a large-scale longitudinal survey database to explore how different life factors affect their ability to engage in daily activities. We select and integrate multiple machine models to o...