AIMC Topic: Machine Learning

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Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

Molecules (Basel, Switzerland)
Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two groups of antidepressants that are the first-line treatment for depressive disorder: selective serotonin reuptake inhibitors and serotonin-norepinephrin...

Predicting survival in malignant glioma using artificial intelligence.

European journal of medical research
Malignant gliomas, including glioblastoma, are amongst the most aggressive primary brain tumours, characterised by rapid progression and a poor prognosis. Survival analysis is an essential aspect of glioma management and research, as most studies use...

Exploring the assessment of post-cardiac valve surgery pulmonary complication risks through the integration of wearable continuous physiological and clinical data.

BMC medical informatics and decision making
BACKGROUND: Postoperative pulmonary complications (PPCs) following cardiac valvular surgery are characterized by high morbidity, mortality, and economic cost. This study leverages wearable technology and machine learning algorithms to preoperatively ...

Optimizing hypoglycaemia prediction in type 1 diabetes with Ensemble Machine Learning modeling.

BMC medical informatics and decision making
BACKGROUND: Type 1 diabetes (T1D) is a chronic endocrine disorder characterized by high blood glucose levels, impacting millions of people globally. Its management requires intensive insulin therapy, frequent blood glucose monitoring, and lifestyle a...

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches.

BMC medical informatics and decision making
BACKGROUND: The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).

Retrieval of nicotine content in cigar leaves by remote analysis of aerial hyperspectral combining machine learning methods.

Scientific reports
Cigar leaf is a special type of tobacco plant, which is the raw material for producing high-quality cigars. The content and proportion of nicotine and other composite substances of cigar leaves have a crucial impact on their quality and vary greatly ...

Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction.

Scientific reports
Heart failure is a leading cause of premature death, especially among individuals with a sedentary lifestyle. Early and accurate detection is essential to prevent the progression of this situation. However, many existing prediction systems failed to ...

Evaluating waist-to-hip ratio in youth using frequency-modulated continuous wave radar and machine learning.

Scientific reports
Waist-to-hip ratio (WHR) is an essential predictor of cardiometabolic diseases, but traditional tape-based WHR measurements in children and adolescents can cause discomfort due to direct contact and are prone to measurer variation. This study aimed t...

A novel hybrid inception-xception convolutional neural network for efficient plant disease classification and detection.

Scientific reports
Plants are essential at all stages of living things. Plant pests, diseases, and symptoms are most regularly visible in plant leaves and fruits and sometimes within the roots. Yet, their diagnosis by experts in the laboratory is expensive, tedious, an...