AIMC Topic: Machine Learning

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User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Precision cancer medicine is dependent on accurate prediction of disease and treatment outcome, requiring integration of clinical, imaging and interventional knowledge. User controlled pipelines are capable of feature integration with varied...

Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

Computer methods and programs in biomedicine
INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to reach shared after-care decisions for recovery or rehabilita...

Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches.

International journal of molecular sciences
A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with...

Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.

Current diabetes reports
PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis, and management of diabetes and its complications. Although various models of ML have been developed, most have not led to practical solutions for rea...

Predicting future onset of depression among community dwelling adults in the Republic of Korea using a machine learning algorithm.

Neuroscience letters
Because depression has high prevalence and cause enduring disability, it is important to predict onset of depression among community dwelling adults. In this study, we aimed to build a machine learning-based predictive model for future onset of depre...

Transient-evoked otoacoustic emission signals predicting outcomes of acute sensorineural hearing loss in patients with Ménière's disease.

Acta oto-laryngologica
Fluctuating hearing loss is characteristic of Ménière's disease (MD) during acute episodes. However, no reliable audiometric hallmarks are available for counselling the hearing recovery possibility. To find parameters for predicting MD hearing outco...

Comparing Logistic Regression Models with Alternative Machine Learning Methods to Predict the Risk of Drug Intoxication Mortality.

International journal of environmental research and public health
(1) Medical research has shown an increasing interest in machine learning, permitting massive multivariate data analysis. Thus, we developed drug intoxication mortality prediction models, and compared machine learning models and traditional logistic ...

Machine learning to predict early recurrence after oesophageal cancer surgery.

The British journal of surgery
BACKGROUND: Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This s...

Prediction of vaginal birth after cesarean deliveries using machine learning.

American journal of obstetrics and gynecology
BACKGROUND: Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliver...