AIMC Topic: Machine Learning

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Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.

Biological psychiatry
Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed in samples of children school-aged or older. Neverth...

Exactech Equinoxe anatomic versus reverse total shoulder arthroplasty for primary osteoarthritis: case controlled comparisons using the machine learning-derived Shoulder Arthroplasty Smart score.

Journal of shoulder and elbow surgery
BACKGROUND: The role of reverse total shoulder arthroplasty (rTSA) for glenohumeral osteoarthritis (GHOA) with an intact rotator cuff remains unclear with prior investigations demonstrating similar patient-reported outcome measures (PROMs) to anatomi...

Heterogeneous treatment effects analysis for social scientists: A review.

Social science research
Social scientists have long been interested in the varying responses to a specific intervention, motivating the enterprise of heterogeneous treatment effects (HTE) analysis. Over the past five decades, the rapid development of HTE methods, from conve...

Researcher reasoning meets computational capacity: Machine learning for social science.

Social science research
Computational power and big data have created new opportunities to explore and understand the social world. A special synergy is possible when social scientists combine human attention to certain aspects of the problem with the power of algorithms to...

Addressing the Challenges and Barriers to the Integration of Machine Learning into Clinical Practice: An Innovative Method to Hybrid Human-Machine Intelligence.

Sensors (Basel, Switzerland)
Machine learning (ML) models have proven their potential in acquiring and analyzing large amounts of data to help solve real-world, complex problems. Their use in healthcare is expected to help physicians make diagnoses, prognoses, treatment decision...

Machine Learning and Swarm Optimization Algorithm in Temperature Compensation of Pressure Sensors.

Sensors (Basel, Switzerland)
The main temperature compensation method for MEMS piezoresistive pressure sensors is software compensation, which processes the sensor data using various algorithms to improve the output accuracy. However, there are few algorithms designed for sensor...

What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health.

International journal of molecular sciences
The idea of a digital twin has recently gained widespread attention. While, so far, it has been used predominantly for problems in engineering and manufacturing, it is believed that a digital twin also holds great promise for applications in medicine...

Bioinspired and Low-Power 2D Machine Vision with Adaptive Machine Learning and Forgetting.

ACS nano
Natural intelligence has many dimensions, with some of its most important manifestations being tied to learning about the environment and making behavioral changes. In primates, vision plays a critical role in learning. The underlying biological neur...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

European journal of medical research
Sepsis is an inflammation caused by the body's systemic response to an infection. The infection could be a result of many diseases, such as pneumonia, urinary tract infection, and other illnesses. Some of its symptoms are fever, tachycardia, tachypne...