AIMC Topic: Machine Learning

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Using Deep Learning to Recognize Therapeutic Effects of Music Based on Emotions.

Sensors (Basel, Switzerland)
Music is important in everyday life, and music therapy can help treat a variety of health issues. Music listening is a technique used by music therapists in various clinical treatments. As a result, music therapists must have an intelligent system at...

FedSepsis: A Federated Multi-Modal Deep Learning-Based Internet of Medical Things Application for Early Detection of Sepsis from Electronic Health Records Using Raspberry Pi and Jetson Nano Devices.

Sensors (Basel, Switzerland)
The concept of the Internet of Medical Things brings a promising option to utilize various electronic health records stored in different medical devices and servers to create practical but secure clinical decision support systems. To achieve such a s...

Machine learning in general practice: scoping review of administrative task support and automation.

BMC primary care
BACKGROUND: Artificial intelligence (AI) is increasingly used to support general practice in the early detection of disease and treatment recommendations. However, AI systems aimed at alleviating time-consuming administrative tasks currently appear l...

Machine learning toward high-performance electrochemical sensors.

Analytical and bioanalytical chemistry
The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single...

Review of Machine Learning and Artificial Intelligence (ML/AI) for the Pediatric Neurologist.

Pediatric neurology
Artificial intelligence (AI) and a popular branch of AI known as machine learning (ML) are increasingly being utilized in medicine and to inform medical research. This review provides an overview of AI and ML (AI/ML), including definitions of common ...

Big data and machine learning driven bioprocessing - Recent trends and critical analysis.

Bioresource technology
Given the potential of machine learning algorithms in revolutionizing the bioengineering field, this paper examined and summarized the literature related to artificial intelligence (AI) in the bioprocessing field. Natural language processing (NLP) wa...

Application of artificial intelligence to stereotactic radiosurgery for intracranial lesions: detection, segmentation, and outcome prediction.

Journal of neuro-oncology
BACKGROUND: Rapid evolution of artificial intelligence (AI) prompted its wide application in healthcare systems. Stereotactic radiosurgery served as a good candidate for AI model development and achieved encouraging result in recent years. This artic...

The Novel Combination of Nano Vector Network Analyzer and Machine Learning for Fruit Identification and Ripeness Grading.

Sensors (Basel, Switzerland)
Fruit classification is required in many smart-farming and industrial applications. In the supermarket, a fruit classification system may be used to help cashiers and customer to identify the fruit species, origin, ripeness, and prices. Some methods,...

Explaining Accurate Predictions of Multitarget Compounds with Machine Learning Models Derived for Individual Targets.

Molecules (Basel, Switzerland)
In drug discovery, compounds with well-defined activity against multiple targets (multitarget compounds, MT-CPDs) provide the basis for polypharmacology and are thus of high interest. Typically, MT-CPDs for polypharmacology have been discovered seren...

Classification of red cell dynamics with convolutional and recurrent neural networks: a sickle cell disease case study.

Scientific reports
The fraction of red blood cells adopting a specific motion under low shear flow is a promising inexpensive marker for monitoring the clinical status of patients with sickle cell disease. Its high-throughput measurement relies on the video analysis of...