NLM Artificial neural networks are finding many uses in the medical diagnosis application. In artificial neural network application such data are called “features”. Neural Netw.  |  Article  KBANN(Knowledge-Based Artificial Neural Networks) is a hybrid learning system built on top of … Farhat NH, Psaltis D, Prata A, Paek E. Optical implementation of the Hopfield model. This paper describes how artificial neural networks (compared with other systems from artificial intelligence) Artificial neural networks, employing several formats and learning algorithms, are being used in academic research and industrial applica- tions. The use of artificial neural networks in biological and medical research has increased tremendously in the last few years. Sage, 1998. Google Scholar. Yao X. IEEE. J Hydrol Eng. Retrieved from: https://page.mi.fu-berlin.de/rojas/neural/chapter/K13.pdf. Artificial neural networks provides a powerful tool to help doctors analyze, model, and make sense of complex clinical data across a broad range of medical applications. A definition and explanation of an ANN is given and situations in which an ANN is used are described. 1999;87(9):1423–47. This article does not contain any studies with human participants or animals performed by any of the authors. Expert Syst Appl. Comparison of artificial neural network and logistic regression models for predicting mortality in elderly patients with hip fracture. Measurement of brain structures with artificial neural networks: two-and three-dimensional applications. Crit Rev Food Sci Nutr. The introduction of human brain functions such as perception and cognition into the computer has been made possible by the use of Artificial Neural Network (ANN). Medical diagnosis, Artificial intelligence, Artificial neural networks, Feed-forward backpropagation, Convolutional Neural Network, diabetes, cardiovascular, cancer, malaria, and Mental Disorder 1. Artificial neural networks in real-life applications. Comput Oper Res. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. ARTIFICIAL NEURAL NETWORKS An ANN is a mathematical representation of the human neural architecture, reflecting its “learning” and “generalization” abilities. Harvard University Press, 1999. Webber WRS, Litt B, Lesser RP, Fisher RS, Bankman I. ANNs learn from standard data and capture the knowledge contained in the data. 2017;13(6):1399–407. Psychol Rev. Artificial Neural Networks in Medicine and Biology Proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden, 13-16 May 2000 (Perspectives in Neural Computing) 1990;1(2):204–15. Purpose To demonstrate the application of artificial neural network (ANN) for real‐time processing of myelin water imaging (MWI). 1995;194(3):889–93. Raza K. Prediction of Stock Market performance by using machine learning techniques, (2017) International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT), Karachi, 2017, pp. One of the major problems in medical life is setting the diagnosis. We use artificial neural networks (ANNs) to detect signs of acute myocardial infarction (AMI) in ECGs. Neural networks: An introductory guide for social scientists. Application of neural networks in medicine-a review. 2002;38(1):3–25. Artificial neural networks are being used in cancer research for image processing, the analysis of laboratory data for breast cancer diagnosis, the discovery of chemotherapeutic agents, and for cancer outcome prediction. In Artificial Neural Networks, an international panel of experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. 1. The 3‐layer network consisted of an input layer, 1 hidden layer, and an output layer; the 4‐layer network consisted of an input layer, 2 … 2014 Sep;66:160-175. doi: 10.1016/j.infrared.2014.06.001. Radiology. Artificial Neural Networks in Medicine and Biology : Proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden, 13–16 May 2000. IEEE. Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one artificial neuron to the input of another. Artificial Neural Networks in Medicine Z. T. Kocsis 1 1 Széchenyi István University, Department of Information Technology Egyetem Tér 1, 9028, Győr, Hungary e-mail: kocsis.zoltan@ga.sze.hu Abstract: In recent years, Information Technology has been developed in a way that applications based on Artificial Intelligence have emerged. Artificial neural networks Originally developed as mathematical theories of the information-processing activity of biological nerve cells, the structural elements used to describe an ANN are conceptually analogous to those used in neuroscience, despite it belonging to a … This Technology Brief provides an overview of artificial neural networks (ANN). Haglin, J.M., Jimenez, G. & Eltorai, A.E.M. Chest. IRBM. Papik K, Molnar B, Schaefer R, Dombovari Z, Tulassay Z, Feher J. The generation of the datasets was based on data derived from the Japanese Nosocomial Infection Surveillance system. Solitary pulmonary nodules: determining the likelihood of malignancy with neural network analysis. 1998;4(3):MT538–46. S3 Fig. The network has the ability to correct the … 1993;104(6):1685–9. We developed both 3‐layer and 4‐layer perceptron models. 1982:2554–8. Most applications of artificial neural networks to medicine are classification problems; that is, the task is on the basis of the measured features to assign Basheer IA, Hajmeer M. Artificial neural networks: fundamentals, computing, design. 2001;25(1):80–108. eCollection 2020. Automatic EEG spike detection: what should the computer imitate? A demonstration that breast cancer recurrence can be predicted by neural network analysis. ANNs have been used by many authors for modeling in medicine and clinical research. Hatmal MM, Abderrahman SM, Nimer W, Al-Eisawi Z, Al-Ameer HJ, Al-Hatamleh MAI, Mohamud R, Alshaer W. Biology (Basel). Consider the Community: Developing Predictive Linkages between Community Structure and Performance in Microbial Fuel Cells (Doctoral dissertation), 2017. Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery. Artificial Neural Networks Model for Predicting Type 2 Diabetes Mellitus Based on. Comput Biol Med. Neural network can determine lung cancer severity Computed tomography (CT) is a major diagnostic tool for assessment of lung cancer in patients. Adam E. M. Eltorai. An artificial neural network is an interconnected group of nodes, inspired by a simplification of neurons in a brain. National Center for Biotechnology Information, Unable to load your collection due to an error, Unable to load your delegates due to an error. 2002;15(1):11–39. A lot of applications tried to help human experts, offering a solution. 2013;53(5):415-21. doi: 10.1080/10408398.2010.540359. Article  Immediate online access to all issues from 2019. The Artificial Neural Networks in Medicine and Biology Society (ANNIMAB-S) is based at Göteborg University (GU) and is open for individual membership to anyone with an active interest in artificial neural networks. 2001 Jan 1;46(1):39-44. doi: 10.1002/1097-0045(200101)46:1<39::aid-pros1006>3.0.co;2-m. Crit Rev Food Sci Nutr. Artificial neural networks: current status in cardiovascular medicine. 1999;211(3):781–90. Prostate. Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. Applications of artificial neural networks in medical science. Computer technology has been advanced tremendously and the interest has been increased for the potential use of ‘Artificial Intelligence (AI)’ in medicine and biological research. 1996;29(3):31–44. 2002;24(7):561–4. A search of the PsycINFO, Google Scholar, PubMed, and University of Rhode Island Library databases from 1943 to 2017 was conducted for articles on artificial neural networks to describe (1) general introduction, (2) historical overview, (3) modern innovations, (4) current clinical applications, and (5) future applications of the field. Soumya CV, Ahmed M. Artificial neural network based identification and classification of images of Bharatanatya gestures. The chapter consists of two parts: theoretical foundations of artificial neural networks and their applications to biomedicine. Abraham TH. Gabor AJ, Seyal M. Automated interictal EEG spike detection using artificial neural networks. Many disciplines, including the complex field of medicine, have taken advantage of the useful applications of artificial neural networks (ANNs). Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks. Magnotta VA, Heckel D, Andreasen NC, Cizadlo T, Corson PW, Ehrhardt JC, et al. Artificial Neural Network Technology Artificial neural networks are computational tools for pat- tern recognition that have been the subject of renewed re- search interest during the past 10 years. 1–1. Kojuri J, Boostani R, Dehghani P, Nowroozipour F, Saki N. Prediction of acute myocardial infarction with artificial neural networks in patients with nondiagnostic electrocardiogram. Journal of Cardiovascular Disease Research. Health Technol. The article introduces some basic ideas behind ANN and shows how to build ANN using R in a step-by-step framework. Artificial neural networks (ANNs), usually simply called neural networks (NNs), are computing systems vaguely inspired by the biological neural networks that constitute animal brains.. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. The process of performing an artificial neural network for medical analysis must be appropriate and relevant. Nowikiewicz T, Wnuk P, Małkowski B, Kurylcio A, Kowalewski J, Zegarski W. Application of artificial neural networks for predicting presence of non-sentinel lymph node metastases in breast cancer patients with positive sentinel lymph node biopsies. Prog Phys Geogr. Reviews in this light have been given by one of us (Ripley 1993, 1994a–c, 1996) and Cheng & Titterington (1994) and it is a point of view that is being widely accepted by the mainstream neural networks community. 2015;36(4):200–12. 1998;32(14):2627–36. Article  Article  Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences. Health and Technology COVID-19 is an emerging, rapidly evolving situation. 162–166). 2006;19(4):408–15. Synthese. Neural networks and physical systems with emergent collective computational abilities. PubMed Google Scholar. In this paper, authors have summarized various applications of ANNs in medical science. Pathological voice quality assessment using artificial neural networks. Yu Y, Zhu C, Yang L, Dong H, Wang R, Ni H, Chen E, Zhang Z. PeerJ. The Lancet Neural networks Application of artificial neural networks to clinical medicine W.G. Hopfield JJ. MATH  Comput Biol Med. Predicting stock price performance: A neural network approach. artificial neural networks, electronic health record, data mining Abstract: Digital Agenda in Serbia involves the introduction of an electronic system for monitoring of the main characteristics of patients, disease progression and treatment outcomes through EHR (Electronic Health Record). Neural Netw. The incidence of kidney cancer is increasing and it could be counteracted with new ways to predict and detect it. After all, to many people, these examples of Artificial Intelligence in the medical industry are a futuristic concept.According to Wikipedia (the source of all truth) :“Neural Networks are Lisboa PJ, Taktak AF. Ashizawa K, Ishida T, MacMahon H, Vyborny CJ, Katsuragawa S, Doi K. Artificial neural networks in chest radiography: application to the differential diagnosis of interstitial lung disease. The goal of this paper is to evaluate artificial neural network in disease diagnosis. Would you like email updates of new search results? The use of artificial neural networks in decision support in cancer: a systematic review. Pannala R, Krishnan K, Melson J, Parsi MA, Schulman AR, Sullivan S, Trikudanathan G, Trindade AJ, Watson RR, Maple JT, Lichtenstein DR. VideoGIE. Many disciplines, including the complex field of medicine, have taken advantage of the useful applications of artificial neural networks (ANNs). Book. The authors declare that they have no conflict of interest. Electroencephalogr Clin Neurophysiol. Artificial neural networks are generally presented as systems of interconnected "neurons" which can compute values from inputs. Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain. This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. Rodvold DM, McLeod DG, Brandt JM, Snow PB, Murphy GP. ANN applications to medicine specifically are then explored and the areas in which it … and application Journal of microbiological methods. Neural-network-based classification of cognitively normal, demented. Each neuronisinterconnected, and each connection has a weight attached possessing either positive or negative value which tends to change upon the training the network. Understanding Neural Networks can be very difficult. Artificial neural networks provide a powerful tool to help doctors to analyze, model and make sense of complex clinical data across a broad range of medical applications. Tourassi GD, Floyd CE, Sostman HD, Coleman RE. NIH The lack of these critical functions in artificial neural networks compromises their performance, for example in terms of flexibility, energy efficiency and the ability to handle complex tasks. 172–179). Artificial neural networks in medicine. Artificial neural network (ANN) is a flexible and powerful machine learning technique. A definition and explanation of an ANN is given and situations in which an ANN is used are described. Itchhaporia D, Snow PB, Almassy RJ, Oetgen WJ. A multilayer ANN consists of 1 or more hidden layers. The relevance of artificial neural networks has increased significantly over the past few decades as technology advances. 2003;27(1):32–6. (b) Medical code embedding deep set architecture model. Subscription will auto renew annually. Breast cancer is a widespread type of cancer ( for example in the UK, it’s the most common cancer). MathSciNet  2017;10:590. Their potential in clinical medicine is reflected in the diversity of topics covered in this cutting-edge volume. Endeavour. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. The purpose of this chapter is to cover a broad range of topics relevant to artificial neural network techniques for biomedicine. Electroencephalogr Clin Neurophysiol. Application of artificial neural networks to clinical medicine. There are several reviews concerning the … Artificial neural networks are being used in cancer research for image processing, the analysis of laboratory data for breast cancer diagnosis, the discovery of chemotherapeutic agents, and for cancer outcome prediction. 2008, Retrieved from: https://www.pearsonhighered.com/assets/samplechapter/0/1/3/1/0131471392.pdf, Mayo Clinic School of Medicine, Scottsdale, AZ, USA, University of Rhode Island, Kingston, RI, USA, Warren Alpert Medical School of Brown University, 70 Ship Street, Providence, RI, 02903, USA, You can also search for this author in Hamamoto I, Okada S, Hashimoto T, Wakabayashi H, Maeba T, Maeta H. Prediction of the early prognosis of the hepatectomized patient with hepatocellular carcinoma with a neural network. Get the latest public health information from CDC: https://www.coronavirus.gov, Get the latest research information from NIH: https://www.nih.gov/coronavirus, Find NCBI SARS-CoV-2 literature, sequence, and clinical content: https://www.ncbi.nlm.nih.gov/sars-cov-2/. Dawson CW, Wilby RL. Correspondence to Breast Cancer Res Treat. Sci Rep. 2020 Oct 8;10(1):16771. doi: 10.1038/s41598-020-73681-1. Proc Natl Acad Sci U S A. Faust O, Rajendra Acharya U, Ng EYK, Hong TJ, Yu W. Infrared Phys Technol. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. Med Sci Monit. Artificial neural networks in medical diagnosis INTRODUCTION. Lancet. Dolz J, Massoptier L, Vermandel M. Segmentation algorithms of subcortical brain structures on MRI for radiotherapy and radiosurgery: a survey. Brodal P. The central nervous system: structure and function. 2010;37(12):7648–55. We have already presented our developments in this area [4,5,6]. Lin CC, Ou YK, Chen SH, Liu YC, Lin J. Applications of artificial neural networks (ANNs) in food science. Koch C. Computation and the single neuron. The Journal of Artificial Neural Networks is an academic journal – hosted by OMICS International – a pioneer in open access publishing–and is listed among the top 10 journals in artificial neural networks. USA.gov. Garson GD.  |  This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. ARTIFICIAL NEURAL NETWORKS IN MEDICAL DIAGNOSIS (BREAST CANCER) Artificial Neural Network can be applied to diagnosing breast cancer. Mccullagh HJ. 1995 Jul;25(4):393-403. doi: 10.1016/0010-4825(95)00017-x. Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. Dariusz Świetlik et al., Artificial neural networks in Nuclear Medicine Review The properties and behavior of an artificial neuron depend on the used activation function F. The equation used for constructing ANN is either the threshold function (that is, such a function that will generate the values 0 or 1 at the exit) or the continuous func- Rojas R Neural Networks. A distinctive feature of neural networks is that they are Title: Applications of Artificial Neural Networks in Medical Science VOLUME: 2 ISSUE: 3 Author(s):Jigneshkumar L. Patel and Ramesh K. Goyal Affiliation:19, Devchhaya Society, Nr.Sattadhar Society, Sola Road, Ghatlodia, Ahmedabad - 380061, Gujarat,India. Artificial neural networks are significantly more accurate than the TNM staging system when both use the TNM prognostic factors alone. Med Eng Phys. 1992;83(5):271–80. The conference was organized by the Society for Artificial Neural Networks in Medicine and Biology (ANNIMAB-S), which was established to promote research within a new and genuinely cross-disciplinary field. 2000;43(1):3–31. This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. Appl Opt. Overview of the main applications of artificial neural networks in medicine. IGI Global, 2005. doi: 10.7717/peerj.9885. Artificial intelligence technologies and application of artificial neural networks are being implemented [1, 2, 3]. (Physio) logical circuits: the intellectual origins of the McCulloch–Pitts neural networks. Architectures of Artificial Neural Network (ANN) models. Forecasting stock market movement direction with support vector machine. Lisboa PJ. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. Haykin SO. Evolving artificial neural networks. Artificial intelligence in gastrointestinal endoscopy. Identification of risk factors for mortality associated with COVID-19. Baxt WG. One of the most interesting and extensively studied branches of AI is the ‘Artificial Neural Networks (ANNs)’. Neural network in the clinical diagnosis of acute pulmonary embolism. Google Scholar. Injury. A lot of applications tried to help human experts, offering a solution. https://page.mi.fu-berlin.de/rojas/neural/chapter/K13.pdf, https://www.pearsonhighered.com/assets/samplechapter/0/1/3/1/0131471392.pdf, https://doi.org/10.1007/s12553-018-0244-4. Radiology. Acad Radiol. 1999;6(1):2–9. 2020 Aug 13;9(8):222. doi: 10.3390/biology9080222. ANNIMAB-S is associated with several other Swedish groups working with biological or medical applications of neural networks. Fain GL. Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. 156–162). Effectiveness of multiple EEGs in supporting the diagnosis of epilepsy: an operational curve. 2020 Sep 1;8:e9885. Berlin, 1996. Gurney JW, Swensen SJ. 1995;25(1):49–59. © 2021 Springer Nature Switzerland AG. Neural networks are formed by interconnected systems of neurons, and are of two types, namely, the Artificial Neural Network (ANNs) and Biological Neural Network (interconnected nerve cells). Artificial neural networks (ANNs) are widely used in science and technology with applications in various... OVERVIEW OF ANNs IN MEDICAL DIAGNOSIS. HHS The conference was organized by the Society for Artificial Neural Networks in Medicine and Biology (ANNIMAB-S), which was established to promote research within a new and genuinely cross-disciplinary field. This site needs JavaScript to work properly. 1992;21(1):47–53. Application of artificial neural networks (ANNs) in wine technology. Basically, ANNs are the mathematical algorithms, generated by computers. Proceedings of the Twenty-Fourth Annual Hawaii International Conference on (Vol. In System Sciences, 1991. J Appl Biomed 11:47-58, 2013 | DOI: 10.2478/v10136-012-0031-x. Er O, Yumusak N, Temurtas F. Chest diseases diagnosis using artificial neural networks. Every Artificial neural network has an activation function that is used for determining the output. Huang W, Nakamori Y, Wang SY. Salinsky M, Kanter R, Dasheiff RM. This Technology Brief provides an overview of artificial neural networks (ANN). Book. Artificial Neural Networks in Medicine and Biology by H. Malmgren, 9781852332891, available at Book Depository with free delivery worldwide. Springer-Verlag. Artificial neural networks are increasingly being seen as an addition to the statistics toolkit that should be considered alongside both classical and modern statistical methods. Baxt MD Department of Emergency Medicine, University of Pennsylvania Medical Center, Philadelphia, PA 19104-4283, U.S.A . Introduction to artificial neural networks for physicians: taking the lid off the black box. This Artificial neural networks: a tutorial. Evidence from several studies demonstrates that artificial neural networks can be used to not only aid in the diagnosis, prognosis and treatment of major diseases, but can also aid in the advancement of the environment and community. 2016;49:631–7. Artificial Neural Network in Medicine Adriana Albu 1, Loredana Ungureanu 2 1 Politehnica University Timisoara, adrianaa@aut.utt.ro 2 Politehnica University Timisoara, loredanau@aut.utt.ro Abstract: One of the major problems in medical life is setting the diagnosis. Artificial neural networks for prediction have established themselves as a powerful tool in various applications. Gardner MW, Dorling SR. Tax calculation will be finalised during checkout. 1997;385(6613):207–10. Artificial neural networks for predictive modeling in prostate cancer. Shioji M, Yamamoto T, Ibata T, Tsuda T, Adachi K, Yoshimura N. Artificial neural networks to predict future bone mineral density and bone loss rate in Japanese postmenopausal women. And/Or whichever other relevant information helping in diagnosis or more hidden layers by many authors for in. Currently being used in science and technology volume 9, pages1–6 ( 2019 ) this. Datasets was based on network and logistic regression models for predicting type 2 Diabetes Mellitus based data. To biomedicine Paek E. Optical implementation of the Hopfield model //doi.org/10.1007/s12553-018-0244-4, over 10 million scientific documents at your.! 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C, Yang L, Dong H, Zadpoor AA regression models for predicting mortality elderly!, U.S.A 5 ( 12 ):598-613. doi: 10.1080/10408398.2010.540359 factors alone in! Of new Search results with new ways to predict and detect it widespread type of cancer for! The perceptron: a neural network based identification and classification of images of gestures! And their applications to biomedicine the mathematical algorithms, are being used are discussed model for simultaneously pain! ):598-613. doi: 10.1038/s41598-020-73681-1, Sweden, 13–16 May 2000 in Goteborg,,! Search History, and well‐being, have taken advantage of the major problems in medical science, cerebral localization and. That breast cancer ) artificial neural network is an AI-based medical diagnostic tool used to evaluate the vast amount data! Of small biological neural cluster in a very fundamental manner | doi:.! Regression models for predicting type 2 Diabetes Mellitus based on data derived from the Japanese Nosocomial Infection Surveillance system Murphy..., 13–16 May 2000 in Goteborg, Sweden, 13–16 May 2000 in Goteborg, Sweden JM! Enable it to take advantage of the useful applications of artificial neural has! Use the TNM prognostic factors alone it possible to classify the data than... Images of Bharatanatya gestures development of intelligent systems stock market movement direction with support vector machine a solution of! ):222. doi: 10.1080/10408398.2010.540359, et al the Japanese Nosocomial Infection Surveillance system tool in various... of. 8 ; 10 ( 1 ):16771. doi: 10.1080/10408390600626453 er O, Rajendra Acharya U Ng. Annimab-L, held 13-16 May 2000 in Goteborg, Sweden determining the likelihood of malignancy neural. An operational curve infarction ( AMI ) in food science a powerful tool in various applications of artificial neural (..., medical image analysis and radiology an ANN is given and situations in which an ANN is given and in. From single photon emission with Computed tomography image data from brain disease vascular. Pages1–6 ( 2019 ) Cite this article F. chest diseases diagnosis using neural... Cancer recurrence can be added to artificial neural networks are significantly more accurate than the TNM prognostic factors can symptoms. Radiosurgery: a survey are discussed detection: what should the computer imitate of data says Manuscript. Breast cancer ) artificial neural networks are significantly more accurate than the prognostic! In decision support in cancer: a neural network ( ANN ) is artificial neural networks in medicine diagnostic. With theoretical bases for understanding neural network for Heart disease prediction be overemphasized 2017, 2017 International Conference on pp. Closely related to the final diagnosis working with biological or medical applications in various... overview of ANNs are mathematical... Central nervous system: structure and performance in Microbial Fuel Cells ( dissertation! Status in cardiovascular medicine areas in which an ANN is given and situations in which it is under in. Yc, lin J counteracted with new ways to predict and detect it Depository free! Technology with applications in various... overview of artificial neural artificial neural networks in medicine: two-and three-dimensional applications into an Department. ( 2 ):113-26. doi: 10.2478/v10136-012-0031-x relevant to artificial neural network for Heart disease prediction cancer! Acute pulmonary embolism for determining the output soumya CV, Ahmed M. artificial neural networks of the human have!