AIMC Topic: Algorithms

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Quantitative analysis of brain herniation from non-contrast CT images using deep learning.

Journal of neuroscience methods
BACKGROUND: Brain herniation is one of the fatal outcomes of increased intracranial pressure (ICP). It is caused due to the presence of hematoma or tumor mass in the brain. Ideal midline (iML) divides the healthy brain into two (right and left) nearl...

Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.

Molecules (Basel, Switzerland)
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...

Classification of Biodegradable Substances Using Balanced Random Trees and Boosted C5.0 Decision Trees.

International journal of environmental research and public health
Substances that do not degrade over time have proven to be harmful to the environment and are dangerous to living organisms. Being able to predict the biodegradability of substances without costly experiments is useful. Recently, the quantitative str...

Aligning text mining and machine learning algorithms with best practices for study selection in systematic literature reviews.

Systematic reviews
BACKGROUND: Despite existing research on text mining and machine learning for title and abstract screening, the role of machine learning within systematic literature reviews (SLRs) for health technology assessment (HTA) remains unclear given lack of ...

Performance Assessment of Classification Algorithms on Early Detection of Liver Syndrome.

Journal of healthcare engineering
In the recent era, a liver syndrome that causes any damage in life capacity is exceptionally normal everywhere throughout the world. It has been found that liver disease is exposed more in young people as a comparison with other aged people. At the p...

One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making.

Surgery
This review describes the steps and conclusions from the development and validation of an artificial intelligence algorithm (the Hypotension Prediction Index), one of the first machine learning predictive algorithms used in the operating room environ...

Artificial intelligence in the diagnosis of pediatric allergic diseases.

Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology
Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decisi...

Deep multi-kernel auto-encoder network for clustering brain functional connectivity data.

Neural networks : the official journal of the International Neural Network Society
In this study, we propose a deep-learning network model called the deep multi-kernel auto-encoder clustering network (DMACN) for clustering functional connectivity data for brain diseases. This model is an end-to-end clustering algorithm that can lea...

Applying Convolutional Neural Networks to Predict the ICD-9 Codes of Medical Records.

Sensors (Basel, Switzerland)
The International Statistical Classification of Disease and Related Health Problems (ICD) is an international standard system for categorizing and reporting diseases, injuries, disorders, and health conditions. Most previously-proposed disease predic...

Automated White Blood Cell Counting in Nailfold Capillary Using Deep Learning Segmentation and Video Stabilization.

Sensors (Basel, Switzerland)
White blood cells (WBCs) are essential components of the immune system in the human body. Various invasive and noninvasive methods to monitor the condition of the WBCs have been developed. Among them, a noninvasive method exploits an optical characte...