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Early Diagnosis

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Skin cancer diagnosis based on optimized convolutional neural network.

Artificial intelligence in medicine
Early detection of skin cancer is very important and can prevent some skin cancers, such as focal cell carcinoma and melanoma. Although there are several reasons that have bad impacts on the detection precision. Recently, the utilization of image pro...

Machine Learning Models for Analysis of Vital Signs Dynamics: A Case for Sepsis Onset Prediction.

Journal of healthcare engineering
OBJECTIVE: Achieving accurate prediction of sepsis detection moment based on bedside monitor data in the intensive care unit (ICU). A good clinical outcome is more probable when onset is suspected and treated on time, thus early insight of sepsis ons...

LiSep LSTM: A Machine Learning Algorithm for Early Detection of Septic Shock.

Scientific reports
Sepsis is a major health concern with global estimates of 31.5 million cases per year. Case fatality rates are still unacceptably high, and early detection and treatment is vital since it significantly reduces mortality rates for this condition. Appr...

Precision screening for familial hypercholesterolaemia: a machine learning study applied to electronic health encounter data.

The Lancet. Digital health
BACKGROUND: Cardiovascular outcomes for people with familial hypercholesterolaemia can be improved with diagnosis and medical management. However, 90% of individuals with familial hypercholesterolaemia remain undiagnosed in the USA. We aimed to accel...

Convolutional neural networks for multi-class brain disease detection using MRI images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The brain disorders may cause loss of some critical functions such as thinking, speech, and movement. So, the early detection of brain diseases may help to get the timely best treatment. One of the conventional methods used to diagnose these disorder...

Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models.

Computers in biology and medicine
Sub-clinical bovine mastitis decreases milk quality and production. Moreover, sub-clinical mastitis leads to the use of antibiotics with consequent increased risk of the emergence of antibiotic-resistant bacteria. Therefore, early detection of infect...

Machine learning for clinical decision support in infectious diseases: a narrative review of current applications.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in infectious diseases (ID).

Emerging role of eHealth in the identification of very early inflammatory rheumatic diseases.

Best practice & research. Clinical rheumatology
Digital health or eHealth technologies, notably pervasive computing, robotics, big-data, wearable devices, machine learning, and artificial intelligence (AI), have opened unprecedented opportunities as to how the diseases are diagnosed and managed wi...

Automated detection and classification of early AMD biomarkers using deep learning.

Scientific reports
Age-related macular degeneration (AMD) affects millions of people and is a leading cause of blindness throughout the world. Ideally, affected individuals would be identified at an early stage before late sequelae such as outer retinal atrophy or exud...