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Do machine learning methods solve the main pitfall of linear regression in dental age estimation?

Forensic science international
INTRODUCTION: Age estimation is crucial in forensic and anthropological fields. Teeth, are valued for their resilience to environmental factors and their preservation over time, making them essential for age estimation when other skeletal remains det...

A novel case-based reasoning system for explainable lung cancer diagnosis.

Computers in biology and medicine
Lung cancer is a leading cause of cancer death worldwide. The survival rate is generally higher when this disease is detected in its early stages. Advances in artificial intelligence (AI) have enabled the development of decision support systems that ...

Accurate Arrhythmia Classification with Multi-Branch, Multi-Head Attention Temporal Convolutional Networks.

Sensors (Basel, Switzerland)
Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for arrhythmia diagnosis. The subtle differences in characteristics among various types of arrhythmias, coupled with class imbalance issues in datasets, ...

Detecting cardiovascular diseases using unsupervised machine learning clustering based on electronic medical records.

BMC medical research methodology
BACKGROUND: Electronic medical records (EMR)-trained machine learning models have the potential in CVD risk prediction by integrating a range of medical data from patients, facilitate timely diagnosis and classification of CVDs. We tested the hypothe...

Accuracy of symptom checker for the diagnosis of sexually transmitted infections using machine learning and Bayesian network algorithms.

BMC infectious diseases
BACKGROUND: A significant proportion of individuals with symptoms of sexually transmitted infection (STI) delay or avoid seeking healthcare, and digital diagnostic tools may prompt them to seek healthcare earlier. Unfortunately, none of the currently...

Predicting maternal risk level using machine learning models.

BMC pregnancy and childbirth
BACKGROUND: Maternal morbidity and mortality remain critical health concerns globally. As a result, reducing the maternal mortality ratio (MMR) is part of goal 3 in the global sustainable development goals (SDGs), and previously, it was an important ...

Machine learning-based predictive models for perioperative major adverse cardiovascular events in patients with stable coronary artery disease undergoing noncardiac surgery.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate prediction of perioperative major adverse cardiovascular events (MACEs) is crucial, as it not only aids clinicians in comprehensively assessing patients' surgical risks and tailoring personalized surgical and periop...

A supervised machine learning statistical design of experiment approach to modeling the barriers to effective snakebite treatment in Ghana.

PLoS neglected tropical diseases
BACKGROUND: Snakebite envenoming is a serious condition that affects 2.5 million people and causes 81,000-138,000 deaths every year, particularly in tropical and subtropical regions. The World Health Organization has set a goal to halve the deaths an...

A machine learning approach for identifying anatomical biomarkers of early mild cognitive impairment.

PeerJ
BACKGROUND: Alzheimer's Disease (AD) poses a major challenge as a neurodegenerative disorder, and early detection is critical for effective intervention. Magnetic resonance imaging (MRI) is a critical tool in AD research due to its availability and c...

A novel strategy for the MPPT in a photovoltaic system via sliding modes control.

PloS one
This paper proposes a robust maximum power point tracking algorithm based on a super twisting sliding modes controller. The underlying idea is solving the classical trajectory tracking control problem where the maximum power point defines the referen...