AIMC Topic: Machine Learning

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Employment of Ensemble Machine Learning Methods for Human Activity Recognition.

Journal of healthcare engineering
The endeavor to detect human activities and behaviors is targeted as a real-time detection mechanism that tends to predict the form of human motions and actions. Though sensors like accelerometer and gyroscopes are noticeable in human motion detectio...

Artificial intelligence in adrenal imaging: A critical review of current applications.

Diagnostic and interventional imaging
In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps f...

Machine learning methods for pK prediction of small molecules: Advances and challenges.

Drug discovery today
The acid-base dissociation constant (pK) is a fundamental property influencing many ADMET properties of small molecules. However, rapid and accurate pK prediction remains a great challenge. In this review, we outline the current advances in machine-l...

Precision Medicine Approaches with Metabolomics and Artificial Intelligence.

International journal of molecular sciences
Recent technological innovations in the field of mass spectrometry have supported the use of metabolomics analysis for precision medicine. This growth has been allowed also by the application of algorithms to data analysis, including multivariate and...

Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration.

International journal of molecular sciences
In the current study, we introduce an integrative machine learning strategy for the autonomous molecular design of protein kinase inhibitors using variational autoencoders and a novel cluster-based perturbation approach for exploration of the chemica...

Clinlabomics: leveraging clinical laboratory data by data mining strategies.

BMC bioinformatics
The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of ...

Vegetation detection using vegetation indices algorithm supported by statistical machine learning.

Environmental monitoring and assessment
In precision agriculture (PA), the usage of image processing, artificial intelligence, data analysis, and internet of things provides an increase in efficiency, energy, and time saving. In image processing-based applications, vegetation detection, in...

Logistics Finance Collaborative Development Model Based on Machine Learning.

Computational intelligence and neuroscience
In the context of rapid social development, a logistics financial model that can meet the financing needs of small and medium-sized enterprises and has high returns is widely used in all aspects of the logistics financial industry. Logistics finance ...

Use of artificial intelligence to identify data elements for The Japanese Orthopaedic Association National Registry from operative records.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
BACKGROUND: The Japanese Orthopaedic Association National Registry (JOANR) was recently launched in Japan and is expected to improve the quality of medical care. However, surgeons must register ten detailed features for total hip arthroplasty, which ...

From real-world electronic health record data to real-world results using artificial intelligence.

Annals of the rheumatic diseases
With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study designs because it captures almost the complete variety...