AIMC Topic: Machine Learning

Clear Filters Showing 23971 to 23980 of 34417 articles

Recent advances in physical reservoir computing: A review.

Neural networks : the official journal of the International Neural Network Society
Reservoir computing is a computational framework suited for temporal/sequential data processing. It is derived from several recurrent neural network models, including echo state networks and liquid state machines. A reservoir computing system consist...

Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data.

Journal of affective disorders
OBJECTIVE: Major depression disorder (MDD) is one of the most prevalent mental disorders worldwide. Diagnosing depression in the early stage is crucial to treatment process. However, due to depression's comorbid nature and the subjectivity in diagnos...

Machine Learning for Prediction of Posttraumatic Stress and Resilience Following Trauma: An Overview of Basic Concepts and Recent Advances.

Journal of traumatic stress
Posttraumatic stress responses are characterized by a heterogeneity in clinical appearance and etiology. This heterogeneity impacts the field's ability to characterize, predict, and remediate maladaptive responses to trauma. Machine learning (ML) app...

PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach.

BMC systems biology
BACKGROUND: Numerous experimental results have indicated that microRNAs (miRNAs) play a vital role in biological processes, as well as outbreaks of diseases at the molecular level. Despite their important role in biological processes, knowledge regar...

Minimalistic Approach to Coreference Resolution in Lithuanian Medical Records.

Computational and mathematical methods in medicine
Coreference resolution is a challenging part of natural language processing (NLP) with applications in machine translation, semantic search and other information retrieval, and decision support systems. Coreference resolution requires linguistic prep...

Predicting Ewing Sarcoma Treatment Outcome Using Infrared Spectroscopy and Machine Learning.

Molecules (Basel, Switzerland)
BACKGROUND: Improved outcome prediction is vital for the delivery of risk-adjusted, appropriate and effective care to paediatric patients with Ewing sarcoma-the second most common paediatric malignant bone tumour. Fourier transform infrared (FTIR) sp...

Machine learning in medicine: a practical introduction.

BMC medical research methodology
BACKGROUND: Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providi...

Resting state connectivity best predicts alcohol use severity in moderate to heavy alcohol users.

NeuroImage. Clinical
BACKGROUND: In the United States, 13% of adults are estimated to have alcohol use disorder (AUD). Most studies examining the neurobiology of AUD treat individuals with this disorder as a homogeneous group; however, the theories of the neurocircuitry ...

A scalable machine learning approach for measuring violent and peaceful forms of political protest participation with social media data.

PloS one
In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistic...

Prediction of cervical spine injury in young pediatric patients: an optimal trees artificial intelligence approach.

Journal of pediatric surgery
BACKGROUND: Cervical spine injuries (CSI) are a major concern in young pediatric trauma patients. The consequences of missed injuries and difficulties in injury clearance for non-verbal patients have led to a tendency to image young children. Imaging...