
CREDIT
Artur Luczak
Getting to the doctor’s office for a check-up can be challenging for someone with a neurological disorder that impairs their movement, such as a stroke. But what if the patient could just take a video clip of their movements with a smart phone and forward the results to their doctor?
Work by Dr Hardeep Ryait and colleagues at CCBN-University of Lethbridge in Alberta, Canada, publishing November 21 in the open-access journal PLOS Biology, shows how this might one day be possible.
Using rats that had incurred a stroke that affected the movement of their fore-limbs, the scientists first asked experts to score the rats’ degree of impairment based on how they reached for food. Then they input this information into a state-of-the-art deep neural network so that it could learn to score the rats’ reaching movements with human-expert accuracy. When the network was subsequently given video footage from a new set of rats reaching for food, it was then also able to score their impairments with similar human-like accuracy. The same program proved able to score other tests given to rats and mice, including tests of their ability to walk across a narrow beam and to pull a string to obtain a food reward.
Artificial neural networks are currently used to drive cars, to interpret video surveillance and to monitor and regulate traffic. This revolution in the use of artificial neural networks has encouraged behavioural neuroscientists to use such networks for scoring the complex behaviour of experimental subjects. Similarly, neurological disorders could also be assessed automatically, allowing quantification of behaviour as part of a check-up or to assess the effects of a drug treatment. This could help avoid the delay that can present a major roadblock to patient treatment.
Altogether, this research indicates that deep neural networks such as this can provide a reliable score for neurological assessment and can assist in designing behavioural metrics to diagnose and monitor neurological disorders. Interestingly, the results revealed that this network can use a wider range of information than that included by experts in a behavioural scoring system. A further distinct contribution of this research is that this network was able to identify features of the behaviour that are most indicative of motor impairments. This is important because this has the potential to improve monitoring the effects of rehabilitation. This method would aid standardization of the diagnosis and monitoring of neurological disorders, and in the future could be used by patients at home for monitoring of daily symptoms.
Learn more: Deep learning to analyze neurological problems
The Latest Google Headlines on:
Analyzing neurological problems
[google_news title=”” keyword=”analyzing neurological problems” num_posts=”10″ blurb_length=”0″ show_thumb=”left”]
The Latest Bing News on:
Analyzing neurological problems
- America's Best Orthopedic Hospitals 2024on July 25, 2024 at 5:40 am
Statista and Newsweek are proud to provide the list of America's Best Orthopedic Hospitals 2024. This ranking awards leading hospitals providing orthopedic care in the United States.
- America's Best Neurological Hospitals 2024on July 25, 2024 at 5:34 am
Statista and Newsweek are proud to provide the list of America's Best Neurological Hospitals 2024. This ranking awards leading hospitals providing cardiac care in the United States.
- Ageing Europe - It’s time we prioritised neurological conditionson July 25, 2024 at 3:31 am
Europeans are living longer than ever before – tangible proof of the phenomenal advancements in science and healthcare.1,2 However, it comes with a paradoxical rise in nervous system disorders, with ...
- Global Therapeutic Apheresis Market Poised for Remarkable Growth, Projected to Reach USD 5.26 Billion by 2033on July 24, 2024 at 11:35 pm
Therapeutic Apheresis Market is expected to reaching an estimated USD 5,264.4 million by 2033 a robust CAGR of 6.8%.
- Dr. Newton Howard Joins Vannadium as Advisor, Fast-Tracking Solutions for Neurological Disorderson July 24, 2024 at 7:35 pm
ARLINGTON, VA / ACCESSWIRE / July 24, 2024 / Vannadium, Inc ., a leader in advanced blockchain and DeepTech innovation, is pleased to announce that Dr. Newton Howard, renowned neuroscientist and ...
- How Machine Learning Transforms Functional Neurological Disorder Classification?on July 24, 2024 at 3:32 pm
Machine learning is revolutionizing the classification of functional neurological disorder (FND) by analyzing complex brain patterns with high precision.
- Swiss Company Magnes Receives CE Mark MDR Class Iia For NUSHU Smart Shoes For Neurological Disorderson July 24, 2024 at 12:12 am
Magnes NUSHU The Swiss company and its solution focus on neurological conditions such as Parkinson's disease, Multiple Sclerosis, and ot ...
- Radiopharmaceuticals Market Size Is Set To Grow By USD 6.28 Billion From ...on July 18, 2024 at 8:44 pm
This radiopharmaceuticals market report extensively covers market segmentation by ...
- Atomic force microscopy in the characterization and clinical evaluation of neurological disorderson July 15, 2024 at 1:50 pm
Neurological disorders are becoming an increasingly significant societal burden, highlighting the critical need for improved diagnostic and therapeutic approaches. Atomic force microscopy (AFM), known ...
- Accurate and continuous remote monitoring of step length can be a sensitive marker for neurological diseases and agingon July 15, 2024 at 11:50 am
The researchers: "Step length is a sensitive and non-invasive measure of a wide range of problems associated with aging, cognitive decline, and many neurological diseases ... the various models could ...
The Latest Google Headlines on:
Deep learning
[google_news title=”” keyword=”deep learning” num_posts=”10″ blurb_length=”0″ show_thumb=”left”]
The Latest Bing News on:
Deep learning
- Deep Learning without Compromising Confidentialityon July 24, 2024 at 1:00 pm
Companies don’t need to share data but can adopt a protocol to train and share a model without revealing their proprietary data.
- Scientists use machine learning to explore effects of cushion gases on underground hydrogen storageon July 23, 2024 at 2:17 pm
Los Alamos National Laboratory scientists are developing powerful machine learning models—an application of artificial intelligence—to simulate underground hydrogen storage operations under various ...
- Machine learning method uses nonlinear optics and structured light to expand information network accuracy and capacityon July 23, 2024 at 10:20 am
Structured light can significantly enhance information capacity, due to its coupling of spatial dimensions and multiple degrees of freedom. In recent years, the combination of structured light ...
- News tagged with deep learningon July 22, 2024 at 5:00 pm
A research team has developed a novel method combining computer vision and deep learning to phenotype drought-stressed poplar saplings, achieving 99% accuracy in variety identification and 76% ...
- Advanced deep learning and UAV imagery boost precision agriculture for future food securityon July 17, 2024 at 10:58 am
A research team has investigated the efficacy of AlexNet, an advanced Convolutional Neural Network (CNN) variant, for automatic crop classification using high-resolution aerial imagery from UAVs.
- Deep learning approach enhances HER2 scoring in breast canceron July 17, 2024 at 9:51 am
The human epidermal growth factor receptor 2 (HER2) is a critical protein in the growth of cancer cells, and its expression level is a vital indicator of breast cancer aggressiveness. Traditionally, ...
- At the Crossroads of Innovation: Embracing AI to Foster Deep Learning in the College Classroomon July 17, 2024 at 7:04 am
I therefore want to suggest that we are at a fundamental crossroads in higher education—our own forked-road moment. We must fundamentally rethink how teaching and learning are done in college and ...
- Innovative deep learning model enhances maize phenotype detection and crop managementon July 6, 2024 at 5:00 pm
A research team developed the Point-Line Net, a deep learning method based on the Mask R-CNN framework, to automatically recognize maize field images and determine the number and growth trajectory of ...
- Deep learning for early osteoporosis risk predictionon June 27, 2024 at 5:00 pm
Tulane University researchers made progress toward that vision by developing a new deep learning algorithm that outperformed existing computer-based osteoporosis risk prediction methods ...