Artificial Intelligence and Neurology

Computers and information technology has played a pivotal role in the advancement of healthcare. Artificial Intelligence (AI) in medicine has significantly evolved over the last few decades, now making it possible to initiate its involvement in real world clinical practice. AI can also be incorporated in a personalized, integrated, adaptive and context aware environment creating the so called Ambient Intelligence (AmI). Neurology is a discipline of medicine that deals with the disorders of nervous system. Large amount of literature exist in regards to utilization of AI and AmI in several aspects of neurology. Using AmI, individual’s neurological function can be monitored around the clock for early recognition of neurological disorders. Electroencephalography and electromyography data can be interpreted by AI with high accuracy. Treatment responses can be monitored objectively by AmI in many conditions like movement disorders and epilepsy. Large quantity of data produced in the neurocritical care units can be processed by AI for better monitoring, treatment and outcome prediction. AI can reduce the cost of care and may potentially benefit remote parts of the world by playing role of an expert adviser. In this brief article, author has discussed the application and potential of AI and AmI in neurology. Some obstacles in their development are briefly discussed and several speculations about their future are made.

[1]  H. Asadi,et al.  Machine Learning for Outcome Prediction of Acute Ischemic Stroke Post Intra-Arterial Therapy , 2014, PloS one.

[2]  ShyamPrabhakaran,et al.  Intravenous Thrombolysis for Stroke Increases Over Time at Primary Stroke Centers , 2012 .

[3]  L. Schwamm,et al.  Telestroke increases use of acute stroke therapy. , 2012, Current opinion in neurology.

[4]  R. Sacco,et al.  Projected costs of ischemic stroke in the United States , 2006, Neurology.

[5]  Jit Biswas,et al.  An Adaptable and Flexible Framework for Assistive Living of Cognitively Impaired People , 2014, IEEE Journal of Biomedical and Health Informatics.

[6]  G. Lightbody,et al.  EEG-based neonatal seizure detection with Support Vector Machines , 2011, Clinical Neurophysiology.

[7]  Nikolaos G. Bourbakis,et al.  A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[8]  B. Cotton,et al.  Treatments for reversing warfarin anticoagulation in patients with acute intracranial hemorrhage: a structured literature review , 2011, International journal of emergency medicine.

[9]  Sundaresan Jayaraman,et al.  Smart Textile-Based Wearable Biomedical Systems: A Transition Plan for Research to Reality , 2010, IEEE Transactions on Information Technology in Biomedicine.

[10]  R A Miller,et al.  Ethical and legal issues related to the use of computer programs in clinical medicine. , 1985, Annals of internal medicine.

[11]  Laurent Beydon,et al.  Closed-Loop Coadministration of Propofol and Remifentanil Guided by Bispectral Index: A Randomized Multicenter Study , 2011, Anesthesia and analgesia.

[12]  G D Puri,et al.  Closed-Loop Anaesthesia Delivery System (CLADSTM) using Bispectral Index: A Performance Assessment Study , 2007, Anaesthesia and intensive care.

[13]  Shyamal Patel,et al.  Wearable Wireless Sensor Network to Assess Clinical Status in Patients with Neurological Disorders , 2007, International Symposium on Information Processing in Sensor Networks.

[14]  M. Janda,et al.  Clinical evaluation of a simultaneous closed‐loop anaesthesia control system for depth of anaesthesia and neuromuscular blockade * , 2011, Anaesthesia.

[15]  Luca Palmerini,et al.  Balance Testing With Inertial Sensors in Patients With Parkinson's Disease: Assessment of Motor Subtypes , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[16]  Chris D. Nugent,et al.  A Predictive Model for Assistive Technology Adoption for People With Dementia , 2014, IEEE Journal of Biomedical and Health Informatics.

[17]  F. Horak,et al.  Role of Body-Worn Movement Monitor Technology for Balance and Gait Rehabilitation , 2014, Physical Therapy.

[18]  Weidong Zhou,et al.  Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[19]  Alan C. Evans,et al.  A fully automatic and robust brain MRI tissue classification method , 2003, Medical Image Anal..

[20]  Divya Sharma,et al.  Body area networks: A survey , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).

[21]  Josh Bongard,et al.  C L I N I C a L a R T I C L E , 2022 .

[22]  F. Mohd-Yasin,et al.  Techniques of EMG signal analysis: detection, processing, classification and applications , 2006, Biological Procedures Online.

[23]  M. Czosnyka,et al.  Fuzzy pattern classification of hemodynamic data can be used to determine noninvasive intracranial pressure. , 2005, Acta neurochirurgica. Supplement.

[24]  B. Ouyang,et al.  Intravenous Thrombolysis for Stroke Increases Over Time at Primary Stroke Centers , 2012, Stroke.

[25]  Gisbert Schneider,et al.  Support vector machine applications in bioinformatics. , 2003, Applied bioinformatics.

[26]  A. Aertsen,et al.  Detecting Epileptic Seizures in Long-term Human EEG: A New Approach to Automatic Online and Real-Time Detection and Classification of Polymorphic Seizure Patterns , 2008, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[27]  H. E. Pople,et al.  Internist-I, an Experimental Computer-Based Diagnostic Consultant for General Internal Medicine , 1982 .

[28]  J. Sivaswamy,et al.  A method for automatic detection and classification of stroke from brain CT images , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[29]  Peter Szolovits,et al.  The coming of age of artificial intelligence in medicine , 2009, Artif. Intell. Medicine.

[30]  M Muthuraman,et al.  Discrimination of Parkinsonian tremor from essential tremor using statistical signal characterization of the spectrum of accelerometer signal. , 2013, Bio-medical materials and engineering.

[31]  Ishita Basu,et al.  Towards closed-loop deep brain stimulation: Decision tree-based Essential Tremor patient's state classifier and tremor reappearance predictor , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[32]  Eric E. Smith,et al.  Randomized assessment of rapid endovascular treatment of ischemic stroke. , 2015, The New England journal of medicine.

[33]  S. G. Axline,et al.  Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system. , 1975, Computers and biomedical research, an international journal.

[34]  Sabri Koçer,et al.  Classification of Emg Signals Using Neuro-Fuzzy System and Diagnosis of Neuromuscular Diseases , 2010, Journal of Medical Systems.

[35]  Juan J. Nieto,et al.  Fuzzy Logic in Medicine and Bioinformatics , 2006, Journal of biomedicine & biotechnology.

[36]  Rosalind W. Picard,et al.  Convulsive seizure detection using a wrist‐worn electrodermal activity and accelerometry biosensor , 2012, Epilepsia.

[37]  R. Passman,et al.  A Comparison of Atrial Fibrillation Monitoring Strategies After Cryptogenic Stroke (from the Cryptogenic Stroke and Underlying AF Trial). , 2015, The American journal of cardiology.

[38]  Rita Paradiso,et al.  A wearable health care system based on knitted integrated sensors , 2005, IEEE Transactions on Information Technology in Biomedicine.

[39]  Kunjan Patel,et al.  Low power real-time seizure detection for ambulatory EEG , 2009, 2009 3rd International Conference on Pervasive Computing Technologies for Healthcare.

[40]  L. Brochard,et al.  Advanced closed loops during mechanical ventilation (PAV, NAVA, ASV, SmartCare). , 2009, Best practice & research. Clinical anaesthesiology.

[41]  Ishita Basu,et al.  A neural network-based design of an on-off adaptive control for Deep Brain Stimulation in movement disorders , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[42]  N. Ramsey,et al.  Fully Implanted Brain-Computer Interface in a Locked-In Patient with ALS. , 2016, The New England journal of medicine.

[43]  D. Blumenthal,et al.  The benefits of health information technology: a review of the recent literature shows predominantly positive results. , 2011, Health affairs.

[44]  Athanasios V. Vasilakos,et al.  A Survey on Ambient Intelligence in Healthcare , 2013, Proceedings of the IEEE.

[45]  Ronachai Pongthornseri,et al.  Low-cost, 3-dimension, office-based inertial sensors for automated tremor assessment: technical development and experimental verification. , 2014, Journal of Parkinson's disease.

[46]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[47]  J. Kostis,et al.  Delay in Presentation and Evaluation for Acute Stroke: Stroke Time Registry for Outcomes Knowledge and Epidemiology (S.T.R.O.K.E.) , 1997, Stroke.

[48]  Gregorio López,et al.  LOBIN: E-Textile and Wireless-Sensor-Network-Based Platform for Healthcare Monitoring in Future Hospital Environments , 2010, IEEE Transactions on Information Technology in Biomedicine.

[49]  Eric J Feuer,et al.  Projections of the cost of cancer care in the United States: 2010-2020. , 2011, Journal of the National Cancer Institute.

[50]  W. Danning.  Urban China , 2013 .

[51]  Reza Fazel-Rezai,et al.  A Fuzzy Logic System for Seizure Onset Detection in Intracranial EEG , 2012, Comput. Intell. Neurosci..

[52]  S. Rutkove,et al.  Machine learning algorithms to classify spinal muscular atrophy subtypes , 2012, Neurology.

[53]  Cuntai Guan,et al.  Artificial neural network based intracranial pressure mean forecast algorithm for medical decision support , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[54]  Pardeep Kumar,et al.  Security Issues in Healthcare Applications Using Wireless Medical Sensor Networks: A Survey , 2011, Sensors.

[55]  Zelma H. T. Kiss,et al.  Smart watch accelerometry for analysis and diagnosis of tremor , 2014, Journal of Neuroscience Methods.

[56]  Mouli Ramasamy,et al.  Nano- Bio- Textile Sensors with Mobile Wireless Platform for Wearable Health Monitoring of Neurological and Cardiovascular Disorders , 2014 .

[57]  M. N. Shanmukha Swamy,et al.  Model-Based Seizure Detection for Intracranial EEG Recordings , 2012, IEEE Transactions on Biomedical Engineering.

[58]  Jose Salinas,et al.  Closed-loop control of fluid therapy for treatment of hypovolemia. , 2008, The Journal of trauma.

[59]  Upkar Varshney,et al.  Pervasive Healthcare , 2003, Computer.

[60]  Zhaohong Deng,et al.  Transductive domain adaptive learning for epileptic electroencephalogram recognition , 2014, Artif. Intell. Medicine.

[61]  Rosalind W. Picard,et al.  A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity , 2010, IEEE Transactions on Biomedical Engineering.

[63]  M. Morrell.  Responsive cortical stimulation for the treatment of medically intractable partial epilepsy , 2011, Neurology.

[64]  Scott Hamilton,et al.  Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials , 2004, The Lancet.

[65]  J. Proost,et al.  Evaluation of a Closed-Loop Muscle Relaxation Control System , 2005, Anesthesia and analgesia.

[66]  Abdulnasir Hossen,et al.  A neural network approach for feature extraction and discrimination between Parkinsonian tremor and essential tremor. , 2013, Technology and health care : official journal of the European Society for Engineering and Medicine.

[67]  R. Hornung,et al.  Population-based study of wake-up strokes , 2011, Neurology.

[68]  Gerard F Anderson,et al.  Health spending in the United States and the rest of the industrialized world. , 2005, Health affairs.

[69]  P. House.  Responsive cortical stimulation for the treatment of medically intractable partial epilepsy , 2012 .

[70]  Shyamal Patel,et al.  A review of wearable sensors and systems with application in rehabilitation , 2012, Journal of NeuroEngineering and Rehabilitation.

[71]  Luc Barvais,et al.  Titration of Propofol for Anesthetic Induction and Maintenance Guided by the Bispectral Index: Closed-loop versus Manual Control: A Prospective, Randomized, Multicenter Study , 2006, Anesthesiology.

[72]  A. Amin,et al.  Improvement in the information content of the Glasgow Coma Scale for the prediction of full cognitive recovery after head injury using fuzzy logic. , 2000, Surgery.

[73]  Ming-Zher Poh,et al.  Wearable sensors: Opportunities and challenges for low-cost health care , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[74]  J. Eluf-Neto,et al.  A randomized controlled trial comparing a computer-assisted insulin infusion protocol with a strict and a conventional protocol for glucose control in critically ill patients. , 2009, Journal of critical care.

[75]  Chun-An Cheng,et al.  Prediction of the Prognosis of Ischemic Stroke Patients after Intravenous Thrombolysis Using Artificial Neural Networks , 2014, ICIMTH.

[76]  G. Mckhann,et al.  Motion Sensors to Assess and Monitor Medical and Surgical Management of Parkinson Disease. , 2015, World neurosurgery.

[77]  J. Crowcroft,et al.  Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine , 2012, Journal of Neuroscience Methods.

[78]  A. L. T. Truong,et al.  Intravenous thrombolysis. , 2010, International journal of stroke : official journal of the International Stroke Society.

[79]  Dorothy F. Edwards,et al.  Artificial neural networks improve the prediction of mortality in intracerebral hemorrhage , 1999, Neurology.

[80]  Upkar Varshney,et al.  Pervasive Healthcare and Wireless Health Monitoring , 2007, Mob. Networks Appl..

[81]  Marc Wysocki,et al.  Closed-loop ventilation: an emerging standard of care? , 2007, Critical care clinics.

[82]  A. Schulze-Bonhage,et al.  Joining the benefits: Combining epileptic seizure prediction methods , 2010, Epilepsia.

[83]  Fleur Tehrani,et al.  A Dual Closed-Loop Control System for Mechanical Ventilation , 2003, Journal of Clinical Monitoring and Computing.

[84]  Y. Aghakhani,et al.  Seizure detection in intracranial EEG using a fuzzy inference system , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[85]  E. Keeler,et al.  Costs and benefits of health information technology. , 2006, Evidence report/technology assessment.

[86]  Hamid Soltanian-Zadeh,et al.  Predicting final extent of ischemic infarction using an artificial neural network analysis of multiparametric MRI in patients with stroke , 2009, IJCNN.

[87]  Cenk Sahin,et al.  Can Neural Network Able to Estimate the Prognosis of Epilepsy Patients Accorrding to Risk Factors? , 2010, Journal of Medical Systems.

[88]  Kim L Coleman,et al.  Accelerometer monitoring of home- and community-based ambulatory activity after stroke. , 2004, Archives of physical medicine and rehabilitation.

[89]  P. Pasquina,et al.  Sensor technology for smart homes. , 2011, Maturitas.

[90]  A. Cerasa,et al.  Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy , 2014, Journal of Neuroscience Methods.

[91]  Fleur T. Tehrani,et al.  A closed-loop system for control of the fraction of inspired oxygen and the positive end-expiratory pressure in mechanical ventilation , 2012, Comput. Biol. Medicine.

[92]  Svetlana Kipervasser,et al.  A Novel Portable Seizure Detection Alarm System: Preliminary Results , 2011, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[93]  Kris K. Hauser,et al.  Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach , 2013, Artif. Intell. Medicine.

[94]  Jiguang Wang,et al.  Factors Associated With Prehospital Delays in the Presentation of Acute Stroke in Urban China , 2012, Stroke.

[95]  Klaus Fassbender,et al.  Diagnosis and treatment of patients with stroke in a mobile stroke unit versus in hospital: a randomised controlled trial , 2012, The Lancet Neurology.

[96]  Maxime Cannesson,et al.  Closed-Loop Fluid Resuscitation: Robustness Against Weight and Cardiac Contractility Variations , 2013, Anesthesia and analgesia.

[97]  Giandomenico Nollo,et al.  Toward personal eHealth in cardiology. Results from the EPI-MEDICS telemedicine project. , 2005, Journal of electrocardiology.

[98]  Maxime Cannesson,et al.  Review article: closed-loop systems in anesthesia: is there a potential for closed-loop fluid management and hemodynamic optimization? , 2012, Anesthesia and analgesia.

[99]  Hojjat Adeli,et al.  Mixed-Band Wavelet-Chaos-Neural Network Methodology for Epilepsy and Epileptic Seizure Detection , 2007, IEEE Transactions on Biomedical Engineering.

[100]  Babita Pandey,et al.  An integrated intelligent computing model for the interpretation of EMG based neuromuscular diseases , 2009, Expert Syst. Appl..

[101]  Rabab Kreidieh Ward,et al.  Energy-Efficient Data Reduction Techniques for Wireless Seizure Detection Systems , 2014, Sensors.

[102]  Hojjat Adeli,et al.  Principal Component Analysis-Enhanced Cosine Radial Basis Function Neural Network for Robust Epilepsy and Seizure Detection , 2008, IEEE Transactions on Biomedical Engineering.

[103]  H. Crystal,et al.  Thrombolytic utilization for ischemic stroke in US hospitals with neurology residency program , 2013, Neurology.

[104]  A. Krumholz,et al.  Driving Issues in Epilepsy: Past, Present, and Future , 2009, Epilepsy currents.

[105]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[106]  P. Bonato,et al.  Wearable Wireless Sensor Network to Assess Clinical Status in Patients with Neurological Disorders , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[107]  Edward H. Shortliffe,et al.  An Expert System for Oncology Protocol Management , 2005 .