Pub Date : 1900-01-01DOI: 10.4018/978-1-7998-2101-4.ch001
V. Gupta, A. Arora
The health care service industry (also known as a medical industry) is an industry that is comprised of the services related to the safeguarding or enhancement of patient health or provides services to treat patients with medicinal, protective, rehabilitative, and analgesic care. For the last two decades, it has been seen that there are drastic changes in healthcare services through automation, digitalization, technological innovation, and communication. Automation has made a revolutionary change in the healthcare industry and allowed for it to be more cost-effective for the industry to run day-to-day operations. Automation-driven health care activities are free from human fatigue and error, so they can help out to provide consistency, accuracy, and potentially lead to a reduction in patient complications, infections, and deaths. Besides, automation can help hospitals, professionals, and doctors for cost-reduction measures and increased efficiency as part of their monetary benefits.
{"title":"Automation in Healthcare Services","authors":"V. Gupta, A. Arora","doi":"10.4018/978-1-7998-2101-4.ch001","DOIUrl":"https://doi.org/10.4018/978-1-7998-2101-4.ch001","url":null,"abstract":"The health care service industry (also known as a medical industry) is an industry that is comprised of the services related to the safeguarding or enhancement of patient health or provides services to treat patients with medicinal, protective, rehabilitative, and analgesic care. For the last two decades, it has been seen that there are drastic changes in healthcare services through automation, digitalization, technological innovation, and communication. Automation has made a revolutionary change in the healthcare industry and allowed for it to be more cost-effective for the industry to run day-to-day operations. Automation-driven health care activities are free from human fatigue and error, so they can help out to provide consistency, accuracy, and potentially lead to a reduction in patient complications, infections, and deaths. Besides, automation can help hospitals, professionals, and doctors for cost-reduction measures and increased efficiency as part of their monetary benefits.","PeriodicalId":306526,"journal":{"name":"Applications of Deep Learning and Big IoT on Personalized Healthcare Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128395920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-7998-2101-4.ch005
Parul Agarwal, Syed Imtiyaz Hassan, S. Mustafa, Jawed S. Ahmad
This chapter discusses a deep learning and IoE (Internet of Everything) based analytical model for disease detection, prediction and correct treatment for the patient would be proposed. In the proposed model, all the stakeholders, namely doctors, patients, medical staff within a clinic, hospital or a medical institute, would be embedded with micro-sensors. The sensors would in turn sense and capture the information gathered from these sources and the surrounding environment and then send it to a single repository, a base or a server, where it would be stored for further processing. These sensors produce massive amounts of data, which needs to be encrypted as well. Then, in order to improve the effectiveness and accuracy of prediction from the data received from these sensors, deep learning methods are used. Further, the advantages of the proposed model would be explored. To conclude, the limitations, opportunities and future applications of deep learning techniques would be discussed in this chapter.
{"title":"An Effective Diagnostic Model for Personalized Healthcare Using Deep Learning Techniques","authors":"Parul Agarwal, Syed Imtiyaz Hassan, S. Mustafa, Jawed S. Ahmad","doi":"10.4018/978-1-7998-2101-4.ch005","DOIUrl":"https://doi.org/10.4018/978-1-7998-2101-4.ch005","url":null,"abstract":"This chapter discusses a deep learning and IoE (Internet of Everything) based analytical model for disease detection, prediction and correct treatment for the patient would be proposed. In the proposed model, all the stakeholders, namely doctors, patients, medical staff within a clinic, hospital or a medical institute, would be embedded with micro-sensors. The sensors would in turn sense and capture the information gathered from these sources and the surrounding environment and then send it to a single repository, a base or a server, where it would be stored for further processing. These sensors produce massive amounts of data, which needs to be encrypted as well. Then, in order to improve the effectiveness and accuracy of prediction from the data received from these sensors, deep learning methods are used. Further, the advantages of the proposed model would be explored. To conclude, the limitations, opportunities and future applications of deep learning techniques would be discussed in this chapter.","PeriodicalId":306526,"journal":{"name":"Applications of Deep Learning and Big IoT on Personalized Healthcare Services","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129507856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-7998-2101-4.ch004
Alankrita Aggarwal, Dr. Kanwalvir Singh Dhindsa, P. K. Suri
Major challenges to the society are the people have aging populace and occurrence of continual diseases and eruption of transferable diseases. to embark upon these unmet healthcare desires for the quick guess and therapeutic of all the important diseases a new area called health informatics is emerging as an interdisciplinary research which is dealing with the getting hold of, spread, dispensation, to store as well retrieve. Particularly when the industry is acquired the health information by using the unassuming sense and wearable technology is well thought-out as groundwork stone in healthiness industry. According to a reports, sensors can be worn and hooked on clothes which can acquire the health information uninterrupted.
{"title":"Automation in Healthcare","authors":"Alankrita Aggarwal, Dr. Kanwalvir Singh Dhindsa, P. K. Suri","doi":"10.4018/978-1-7998-2101-4.ch004","DOIUrl":"https://doi.org/10.4018/978-1-7998-2101-4.ch004","url":null,"abstract":"Major challenges to the society are the people have aging populace and occurrence of continual diseases and eruption of transferable diseases. to embark upon these unmet healthcare desires for the quick guess and therapeutic of all the important diseases a new area called health informatics is emerging as an interdisciplinary research which is dealing with the getting hold of, spread, dispensation, to store as well retrieve. Particularly when the industry is acquired the health information by using the unassuming sense and wearable technology is well thought-out as groundwork stone in healthiness industry. According to a reports, sensors can be worn and hooked on clothes which can acquire the health information uninterrupted.","PeriodicalId":306526,"journal":{"name":"Applications of Deep Learning and Big IoT on Personalized Healthcare Services","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122287104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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