Artificial Intelligence in Medical Science

Advances in Healthcare Information Systems and Administration - Intelligent Systems for Healthcare Management and Delivery ◽

10.4018/978-1-5225-7071-4.ch014 ◽

2019 ◽

pp. 306-330

Author(s):

Shashwati Mishra ◽

Mrutyunjaya Panda

Keyword(s):

Medical Science ◽

Data Retrieval ◽

Analysis Data ◽

Disease Diagnosis ◽

Human Beings ◽

Science And Engineering ◽

Patient Health Status ◽

Patient Health ◽

Intelligent Devices ◽

Nature Inspired Algorithms

The use of intelligent artificial devices has solved many real-world problems and also improved the living style of human beings. The capability of providing unbiased and accurate result has also increased the demand for these devices. For getting faster and well-organized outcomes, scientists and researchers are giving more and more interest in developing such devices. Use of expert systems, concepts from nature-inspired algorithms, neural networks, genetic algorithms, fuzzy logic, internet of things are used extensively to solve various problems in science and engineering. In medical science these techniques are used for data analysis, disease diagnosis, data retrieval, object detection, pattern analysis, data management, monitoring patient health status by physicians, interactions between patients and physicians, keeping record of the medications of the patients, and so on. This chapter performs a detailed analysis on the use of intelligent devices in medical science and about the root concepts on which these devices are designed.

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Guidelines adherence in the prevention and management of chronic kidney disease in patients with diabetes mellitus on the background of recent European recommendations – a registry-based analysis

BMC Nephrology ◽

10.1186/s12882-021-02394-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Peter Bramlage ◽

Stefanie Lanzinger ◽

Sascha R. Tittel ◽

Eva Hess ◽

Simon Fahrner ◽

...

Keyword(s):

Type 2 Diabetes ◽

Chronic Kidney Disease ◽

Clinical Practice ◽

Kidney Disease ◽

Analysis Data ◽

Disease Diagnosis ◽

Diabetic Patients ◽

European Society Of Cardiology

Abstract Background Recent European Society of Cardiology (ESC)/European Association for the Study of Diabetes (EASD) guidelines provide recommendations for detecting and treating chronic kidney disease (CKD) in diabetic patients. We compared clinical practice with guidelines to determine areas for improvement. Methods German database analysis of 675,628 patients with type 1 or type 2 diabetes, with 134,395 included in this analysis. Data were compared with ESC/EASD recommendations. Results This analysis included 17,649 and 116,747 patients with type 1 and type 2 diabetes, respectively. The analysis showed that 44.1 and 49.1 % patients with type 1 and type 2 diabetes, respectively, were annually screened for CKD. Despite anti-diabetic treatment, only 27.2 % patients with type 1 and 43.5 % patients with type 2 achieved a target HbA1c of < 7.0 %. Use of sodium-glucose transport protein 2 inhibitors (1.5 % type 1/8.7 % type 2 diabetes) and glucagon-like peptide-1 receptor agonists (0.6 % type 1/5.2 % type 2 diabetes) was limited. Hypertension was controlled according to guidelines in 41.1 and 67.7 % patients aged 18–65 years with type 1 and 2 diabetes, respectively, (62.4 vs. 68.4 % in patients > 65 years). Renin angiotensin aldosterone inhibitors were used in 24.0 and 40.9 % patients with type 1 diabetes (micro- vs. macroalbuminuria) and 39.9 and 47.7 %, respectively, in type 2 diabetes. Conclusions Data indicate there is room for improvement in caring for diabetic patients with respect to renal disease diagnosis and treatment. While specific and potentially clinically justified reasons for non-compliance exist, the data may serve well for a critical appraisal of clinical practice decisions.

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Internet of things-based cloud computing platform for analyzing the physical health condition

Technology and Health Care ◽

10.3233/thc-213003 ◽

2021 ◽

pp. 1-15

Author(s):

Mengyao Cui ◽

Seung-Soo Baek ◽

Rubén González Crespo ◽

R. Premalatha

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Health Monitoring ◽

Tracking System ◽

Disease Diagnosis ◽

Health Condition ◽

Computing Platform ◽

Concept Model ◽

Patient Health ◽

Cloud Servers

BACKGROUND: Health monitoring is important for early disease diagnosis and will reduce the discomfort and treatment expenses, which is very relevant in terms of prevention. The early diagnosis and treatment of multiple conditions will improve solutions to the patient’s healthcare radically. A concept model for the real-time patient tracking system is the primary goal of the method. The Internet of things (IoT) has made health systems accessible for programs based on the value of patient health. OBJECTIVE: In this paper, the IoT-based cloud computing for patient health monitoring framework (IoT-CCPHM), has been proposed for effective monitoring of the patients. METHOD: The emerging connected sensors and IoT devices monitor and test the cardiac speed, oxygen saturation percentage, body temperature, and patient’s eye movement. The collected data are used in the cloud database to evaluate the patient’s health, and the effects of all measures are stored. The IoT-CCPHM maintains that the medical record is processed in the cloud servers. RESULTS: The experimental results show that patient health monitoring is a reliable way to improve health effectively.

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PATIENT HEALTH STATUS TRAJECTORIES IN HEART FAILURE WITH RECOVERED EJECTION FRACTION

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(19)31577-3 ◽

2019 ◽

Vol 73 (9) ◽

pp. 970

Author(s):

Peter Wohlfahrt ◽

Jose Nativi-Nicolau ◽

Mingyuan Zhang ◽

Craig Selzman ◽

Tom Greene ◽

...

Keyword(s):

Heart Failure ◽

Health Status ◽

Ejection Fraction ◽

Patient Health Status ◽

Patient Health

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Development and Contextualization of Multicultural Insight-Based Quran Hadith Materials in Madrasah Aliyah

Edukasia Jurnal Penelitian Pendidikan Islam ◽

10.21043/edukasia.v15i2.8045 ◽

2020 ◽

Vol 15 (2) ◽

pp. 293

Author(s):

Sukino Sukino ◽

Wahab Wahab ◽

Ahmad Fauzi Murliji

Keyword(s):

Data Collection ◽

Social Ethics ◽

Field Research ◽

Analysis Data ◽

Study Data ◽

Human Beings ◽

Literature Study ◽

Collection Data ◽

Universal Values ◽

Multicultural Perspective

<p> </p><p class="06IsiAbstrak">Indonesian Muslims are faced with the realities of life that are multi-ethnic, religious, cultural and linguistic. It must be responded critically as early as possible. The understanding of diversity (multiculturalism) should truly be the foundation of all components of the Muslim community without exception for the students. Therefore this paper intends to answer 1) material content of Quran Hadith with a multicultural perspective at Madrasah Aliyah Negeri 2 Pontianak, and 2) Development and contextualization of Qur'an Hadith material in daily life. This research was categorized as field research and literature study. Data collection methods used were observation, interviews and document analysis. Data analysis was through two models, namely content analysis and Miles and Huberman's model which involved analysis steps, namely: data collection, data reduction, data display, and verification. The authors’ findings on this study are that the content of the Quran Hadith with a multicultural perspective in Madrasah Aliyah is carried out by expanding the reading, the meaning of the implementation of tolerance, social ethics, justice, deliberation / democracy concepts which are constructed from the Islamic universal values and moderation (washathiyah) so they can foster a tolerant and empathy (alturism) attitutes to human beings as a manifestation of an obedient servant.</p>

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Impact of Wi-Fi Electromagnetic Waves on Brainwaves

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1079-1080.882 ◽

2014 ◽

Vol 1079-1080 ◽

pp. 882-886 ◽

Cited By ~ 1

Author(s):

Fu Chien Kao ◽

Shin Ping R. Wang ◽

Yun Kai Lin ◽

Chih Chia Chen ◽

Chih Hsun Huang

Keyword(s):

Wireless Communication ◽

Communication Technology ◽

Cognitive Neuroscience ◽

Electromagnetic Waves ◽

Medical Science ◽

Low Frequency ◽

Primary Study ◽

Human Beings ◽

Wireless Internet ◽

Financial Transactions

In the era of wireless communication, WiFi becomes an indispensable accessory to most of us. People use WIFI to interact with the wireless Internet, perform commercial and financial transactions, or conducting recreational activities, etc.Though it offers a more convenient life to people, the strong Electromagnetic waves(EMW) resulted from it endangers human health, that has already turned out to be the primary study for medical science. Furthermore, EMW also attracts concern and panic of the inhabitants living in the surroundings which is filled with high-frequency and low-frequency EMwave. EMW today comes from broadcast towers, the system of the wireless communication, GPS, TVs and defense satellites mostly. Enjoying the convenience resulted from communication technology, people nowadays should also concern about whether EM wave would damage people’s health at the same time. Based on the perspective of cognitive neuroscience, this study mainly focuses on how EM wave produced from WiFi affects subject’s brainwaves under a specific physiological situation. The researcher observes different changing of brainwave when human beings expose in various strength of EM wave, and analyses the affection of EMW toward subject’s brainwaves.

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Biological-Signal-Based User-Interface System for Virtual-Reality Applications for Healthcare

Journal of Sensors ◽

10.1155/2018/9054758 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10

Author(s):

Sang Hun Nam ◽

Ji Yong Lee ◽

Jung Yoon Kim

Keyword(s):

Virtual Reality ◽

User Interface ◽

Virtual Reality Technology ◽

Biological Signal ◽

Patient Health Status ◽

Interface System ◽

Biological Signals ◽

Patient Health ◽

System Module ◽

Tracking Device

Biosignal interfaces provide important data that reveal the physical status of a user, and they are used in the medical field for patient health status monitoring, medical automation, or rehabilitation services. Biosignals can be used in developing new contents, in conjunction with virtual reality, and are important factors for extracting user emotion or measuring user experience. A biological-signal-based user-interface system composed of sensor devices, a user-interface system, and an application that can extract biological-signal data from multiple biological-signal devices and be used by content developers was designed. A network-based protocol was used for unconstrained use of the device so that the biological signals can be freely received via USB, Bluetooth, WiFi, and an internal system module. A system that can extract biological-signal data from multiple biological-signal data and simultaneously extract and analyze the data from a virtual-reality-specific eye-tracking device was developed so that users who develop healthcare contents based on virtual-reality technology can easily use the biological signals.

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