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Human Diseases Detection Based On Machine Learning Algorithms: A Review Nareen O. M. Salim & Adnan Mohsin Abdulazeez

Human Diseases Detection Based On Machine Learning Algorithms: A Review

Author (s)

Nareen O. M. Salim & Adnan Mohsin Abdulazeez

Abstract

­One of the most significant subjects of society is human healthcare. It is looking for the best one and robust disease diagnosis to get the care they need as soon as possible. Other fields, such as statistics and computer science, are needed for the health aspect of searching since this recognition is often complicated. The task of following new approaches is challenging these disciplines, moving beyond the conventional ones. The actual number of new techniques makes it possible to provide a broad overview that avoids particular aspects. To this end, we suggest a systematic analysis of human diseases related to machine learning. This research concentrates on existing techniques related to machine learning growth applied to the diagnosis of human illnesses in the medical field to discover exciting trends, make unimportant predictions, and help decision-making. This paper analyzes unique machine learning algorithms used for healthcare applications to create adequate decision support. This paper intends to reduce the research gap in creating a realistic decision support system for medical applications.

 Keywords: Human disease, Healthcare, Machine learning, Deep learning, Convolutional Neural Networks.

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Title: Human Diseases Detection Based On Machine Learning Algorithms: A Review
Author: Nareen O. M. Salim & Adnan Mohsin Abdulazeez
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4467510
Media: Online
Volume: 5
Issue: 2
Acceptance Date: 19/01/2021
Date of Publication: 25/01/2021
PDF URL: https://ijsab.com/wp-content/uploads/674.pdf
Free download: Available
Page: 102-113
First Page: 102
Last Page: 113
Paper Type: Literature Review
Current Status: Published

 

Cite This Article:

Nareen O. M. Salim & Adnan Mohsin Abdulazeez (2021). Human Diseases Detection Based On Machine Learning Algorithms: A Review. International Journal of Science and Business, 5(2), 102-113. doi: https://doi.org/10.5281/zenodo.4462858

Retrieved from https://ijsab.com/wp-content/uploads/674.pdf

 

About Author (s)

Nareen O. M. Salim, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq.

Adnan Mohsin Abdulazeez (corresponding author), Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email: nareen.mohameed@dpu.edu.krd

 

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DOI: https://doi.org/10.5281/zenodo.4467510

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Impact of IoT Frameworks on Healthcare and Medical Systems Performance Rezgar Hasan Saeed, Hivi Ismat Dino, Lailan M. Haji, Daroon Mudhafer Hamed, Hanan M. Shukur, Omid H. Jader

Impact of IoT Frameworks on Healthcare and Medical Systems Performance

Author (s)

Rezgar Hasan Saeed, Hivi Ismat Dino, Lailan M. Haji, Daroon Mudhafer Hamed, Hanan M. Shukur, Omid H. Jader

Abstract

­

Internet of Thing (IoT) is a system of interconnected calculating equipment, electronically and mechanically and digital equipment delivered with Unique Identifiers and capability of data-transmission through a system without needful of Human-to-Human or Human-to-Computer communication. However, IoMT considered as IoT-program-implementation aimed at medicinal besides healthcare requirements, information gathering also investigation to be studied and observed. This led to proposing extensive scope of fascinating prospective consequences for enterprises: vehicles mileage-sensitivity as well auto-strategy support otherwise prepare it strongly establish in addition description predicted alighting periods towards taking-up travelers. This is due to that its standards are as of now being connected to improve access to the mind, increment the quality of care also, above all decrease the cost of care. An efficient IoT healthcare system aims to give continuous remote checking of patient health conditions, to counteract the basic patient conditions, and to improve personal satisfaction through a smart IoT environment. The trend of this paper is about displaying a detailed survey that addresses the closest previous studies to IoT roles in the healthcare sector. Giving inspiration, confinements looked by specialists, and recommendations proposed to examiners for improving this basic research field, according to detailed comparison among the addressed researches.

 Keywords: Internet of Things, Healthcare, Cloud Computing, Wireless Sensors.

 

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Title: Impact of IoT Frameworks on Healthcare and Medical Systems Performance
Author: Rezgar Hasan Saeed, Hivi Ismat Dino, Lailan M. Haji, Daroon Mudhafer Hamed, Hanan M. Shukur, Omid H. Jader
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4423394
Media: Online
Volume: 5
Issue: 1
Acceptance Date: 26/12/2020
Date of Publication: 07/01/2021
PDF URL: https://ijsab.com/wp-content/uploads/661.pdf
Free download: Available
Page: 115-126
First Page: 115
Last Page: 126
Paper Type: Literature Review
Current Status: Published

 

Cite This Article:

Rezgar Hasan Saeed, Hivi Ismat Dino, Lailan M. Haji, Daroon Mudhafer Hamed, Hanan M. Shukur, Omid H. Jader (2020). Impact of IoT Frameworks on Healthcare and Medical Systems Performance. International Journal of Science and Business, 5(1), 115-126. doi: https://doi.org/10.5281/zenodo.4423394

Retrieved from https://ijsab.com/wp-content/uploads/661.pdf

 

About Author (s)

Rezgar Hasan Saeed (corresponding author), Computer and Technology Education Department, Near east university, Cyprus. rezgarhasan1992@gmail.com

Hivi Ismat Dino, Department of Computer Science, University of Zakho, Kurdistan Region – Iraq, hivi.dino@uoz.edu.krd

Lailan M. Haji, Department of Computer Science, University of Zakho, Kurdistan Region – Iraq, lailan.haji@uoz.edu.krd

Daroon Mudhafer Hamed, Lebanese French University, Erbil – Kurdistan Region – Iraq, daroon.m.h@gmail.com

Hanan M. Shukur, It Department, Al Kitab University, Kirkuk – Iraq, hanan89md@gmail.com

Omid H. Jader, Information System Engineering Dept. Erbil Polytechnic University, Kurdistan Region-Iraq, omid.jader@epu.edu.iq

 

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DOI: https://doi.org/10.5281/zenodo.4423394