AIMC Topic: Machine Learning

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Big data and machine learning in critical care: Opportunities for collaborative research.

Medicina intensiva
The introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready clinical data that can be used to improve patient outcomes and the allocation of resources, as well...

Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatmen...

Machine learning in neurology: what neurologists can learn from machines and vice versa.

Journal of neurology
Artificial intelligence is increasingly becoming a part of everyday life. This raises the question whether clinical neurology can benefit from these novel methods to increase diagnostic accuracy. Several recent studies have used machine learning clas...

Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.

Academic radiology
RATIONALE AND OBJECTIVES: With the growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening, we compare the performance of deep learning computer-aided diagnosis on DBT images to that of conventional full-field digital mammog...

Attributes' Importance for Zero-Shot Pose-Classification Based on Wearable Sensors.

Sensors (Basel, Switzerland)
This paper presents a simple yet effective method for improving the performance of zero-shot learning (ZSL). ZSL classifies instances of unseen classes, from which no training data is available, by utilizing the attributes of the classes. Conventiona...

A Novel Teaching-Learning-Based Optimization with Error Correction and Cauchy Distribution for Path Planning of Unmanned Air Vehicle.

Computational intelligence and neuroscience
Teaching-learning-based optimization (TLBO) algorithm is a novel heuristic method which simulates the teaching-learning phenomenon of a classroom. However, in the later period of evolution of the TLBO algorithm, the lower exploitation ability and the...

Machine Learning Approach to Predicting Stem Cell Donor Availability.

Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation
The success of unrelated donor stem cell transplants depends on not only finding genetically matched donors, but also donor availability. On average 50% of potential donors in the National Marrow Donor Program database are unavailable for a variety o...

Classification of Chicken Parts Using a Portable Near-Infrared (NIR) Spectrophotometer and Machine Learning.

Applied spectroscopy
Identification of different chicken parts using portable equipment could provide useful information for the processing industry and also for authentication purposes. Traditionally, physical-chemical analysis could deal with this task, but some disadv...

Machine-learned selection of psychological questionnaire items relevant to the development of persistent pain after breast cancer surgery.

British journal of anaesthesia
BACKGROUND: Prevention of persistent pain after breast cancer surgery, via early identification of patients at high risk, is a clinical need. Psychological factors are among the most consistently proposed predictive parameters for the development of ...