AIMC Topic: Machine Learning

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ChemBoost: A Chemical Language Based Approach for Protein - Ligand Binding Affinity Prediction.

Molecular informatics
Identification of high affinity drug-target interactions is a major research question in drug discovery. Proteins are generally represented by their structures or sequences. However, structures are available only for a small subset of biomolecules an...

Predicting the Individual Treatment Effect of Neurosurgery for Patients with Traumatic Brain Injury in the Low-Resource Setting: A Machine Learning Approach in Uganda.

Journal of neurotrauma
Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these low-resource settings, effective triage of patients with TBI-including the decision of whether or not to perform neurosurgery-is critical in op...

Machine Learning Modeling for Ultrasonication-Mediated Fermentation of Penicillium brevicompactum to Enhance the Release of Mycophenolic Acid.

Ultrasound in medicine & biology
Described here is the modeling used to improve the mycophenolic acid (MPA) titer from Penicillium brevicompactum using central composite design and a comparatively newer, data-centric approach method k-nearest-neighbor algorithm. The two models for e...

Development of a quantitative systems pharmacology model of chronic kidney disease: metabolic bone disorder.

American journal of physiology. Renal physiology
Chronic kidney disease mineral bone disorder (CKD-MBD) is a virtually universal complication of kidney diseases, starting early in the course of disease and resulting in devastating clinical consequences ranging from bone fragility to accelerated ath...

Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis.

Proceedings of the National Academy of Sciences of the United States of America
Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits; however, distinguishing the clinical phenotype of irritant and all...

Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques.

International journal of environmental research and public health
In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational effici...

Distinction of surgically resected gastrointestinal stromal tumor by near-infrared hyperspectral imaging.

Scientific reports
The diagnosis of gastrointestinal stromal tumor (GIST) using conventional endoscopy is difficult because submucosal tumor (SMT) lesions like GIST are covered by a mucosal layer. Near-infrared hyperspectral imaging (NIR-HSI) can obtain optical informa...

Detection of eye contact with deep neural networks is as accurate as human experts.

Nature communications
Eye contact is among the most primary means of social communication used by humans. Quantification of eye contact is valuable as a part of the analysis of social roles and communication skills, and for clinical screening. Estimating a subject's looki...

Prediction of in-hospital mortality in patients on mechanical ventilation post traumatic brain injury: machine learning approach.

BMC medical informatics and decision making
BACKGROUND: The study aimed to introduce a machine learning model that predicts in-hospital mortality in patients on mechanical ventilation (MV) following moderate to severe traumatic brain injury (TBI).

Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices.

BMC bioinformatics
BACKGROUND: The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology...