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A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records.

BMC medical informatics and decision making
BACKGROUND: Manual coding of phenotypes in brain radiology reports is time consuming. We developed a natural language processing (NLP) algorithm to enable automatic identification of brain imaging in radiology reports performed in routine clinical pr...

External validation of the SORG 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Preoperative survival estimation in spinal metastatic disease helps determine the appropriateness of invasive management. The SORG ML 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease were pre...

Clustering suicides: A data-driven, exploratory machine learning approach.

European psychiatry : the journal of the Association of European Psychiatrists
Methods of suicide have received considerable attention in suicide research. The common approach to differentiate methods of suicide is the classification into "violent" versus "non-violent" method. Interestingly, since the proposition of this dichot...

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol.

BMC psychiatry
BACKGROUND: The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies to collect data and extract relevant information's for patient management. Artificial intelligence (AI) techniques allow processing o...

Multi-task learning for quality assessment of fetal head ultrasound images.

Medical image analysis
It is essential to measure anatomical parameters in prenatal ultrasound images for the growth and development of the fetus, which is highly relied on obtaining a standard plane. However, the acquisition of a standard plane is, in turn, highly subject...

Nonconvulsive epileptic seizure monitoring with incremental learning.

Computers in biology and medicine
Nonconvulsive epileptic seizures (NCSz) and nonconvulsive status epilepticus (NCSE) are two neurological entities associated with increment in morbidity and mortality in critically ill patients. In a previous work, we introduced a method which accura...

Fore-aft resistance applied at the center of mass using a novel robotic interface proportionately increases propulsive force generation in healthy nonimpaired individuals walking at a constant speed.

Journal of neuroengineering and rehabilitation
BACKGROUND: Past studies have utilized external interfaces like resistive bands and motor-generated pulling systems to increase limb propulsion during walking on a motorized treadmill. However, assessing changes in limb propulsion against increasing ...

Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation.

NeuroImage. Clinical
Machine learning-based imaging diagnostics has recently reached or even surpassed the level of clinical experts in several clinical domains. However, classification decisions of a trained machine learning system are typically non-transparent, a major...

Phytochemical analysis and evaluation of the antioxidant and antiproliferative effects of Tucumã oil nanocapsules in breast adenocarcinoma cells (MCF-7).

Natural product research
In this work was to develop an inedited nanocapsule with tucumã oil (). The oil presents of phytosterols (squalene and β-sitosterol), --beta-carotene, acids oleic and palmitic. Antioxidant activity showed a good performance in DPPH and ABTS assays. T...