scholarly journals Accessing the ECG Data of the Apple Watch and Accomplishing Interoperability Through FHIR

2021 ◽  
Author(s):  
Alexander Bartschke ◽  
Yannick Börner ◽  
Sylvia Thun
Keyword(s):  
Health Care ◽  
Efficient Solution ◽  
Medical Data ◽  
Data Standard ◽  
Reference Number ◽  
Iphone Application ◽  
New Treatment ◽  
User Friendly ◽  
Minimal Effort ◽  
Ecg Data

Medical data generated by wearables and smartphones can add value to health care and medical research. This also applies to the ECG data that is created with Apple Watch 4 or later. However, Apple currently does not provide an efficient solution for accessing and sharing ECG raw data in a standardized data format. Our method aims to provide a solution that enables patients to share their Apple Watch’s ECG data with any health care institution via an iPhone application. We achieved this by implementing a parser in Swift that converts the Apple Watch’s raw ECG data into a FHIR observation. Furthermore, we added the capability of transmitting these observations to a specified server and equipping it with the patient’s reference number. The result is a user-friendly iPhone application, enabling patients to share their Apple Watch’s ECG data in a widely known health data standard with minimal effort. This allows the personnel involved in the patient’s treatment to use data that was previously difficult to access for further analyses and processing. Our solution can facilitate research for new treatment methods, for example, utilizing the Apple Watch for continuous monitoring of heart activity and early detection of heart conditions.

scholarly journals Creating Price Indexes for Measuring Productivity in Mental Health Care

2001 ◽  
Vol 4 (1) ◽  
Author(s):  
Susan H. Busch ◽  
Ernst R. Berndt ◽  
Richard G. Frank
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Major Depression ◽  
Price Index ◽  
Time Varying ◽  
Measurement Issues ◽  
The Past ◽  
Price Indexes ◽  
Treatment Technologies ◽  
New Treatment

Economists have long suggested that to be reliable, a preferred medical care price index should employ time-varying weights to measure outcomes-adjusted changes in the price of treating an episode of illness. In this article, we report on several years of research developing alternative indexes for the treatment of the acute phase of major depression, for the period 1991–1996. The introduction of new treatment technologies in the past two decades suggests well-known measurement issues may be prominent in constructing such a price index.We report on the results of four successively re

scholarly journals How Do Machines Learn? Artificial Intelligence as a New Era in Medicine

2021 ◽  
Vol 11 (1) ◽  
pp. 32
Author(s):  
Oliwia Koteluk ◽  
Adrian Wartecki ◽  
Sylwia Mazurek ◽  
Iga Kołodziejczak ◽  
Andrzej Mackiewicz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Medical Data ◽  
General Process ◽  
New Era ◽  
Automated Evaluation ◽  
Machine Learning Applications ◽  
And Training ◽  
Current Standards

With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to make faster and more correct decisions and improving current standards of treatment. Today, machines can analyze, learn, communicate, and understand processed data and are used in health care increasingly. This review explains different models and the general process of machine learning and training the algorithms. Furthermore, it summarizes the most useful machine learning applications and tools in different branches of medicine and health care (radiology, pathology, pharmacology, infectious diseases, personalized decision making, and many others). The review also addresses the futuristic prospects and threats of applying artificial intelligence as an advanced, automated medicine tool.

The Potential Role of Psychedelic Drugs in Mental Health Care of the Future

2021 ◽  
Author(s):  
Gerhard Gründer ◽  
Henrik Jungaberle
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Mental Health Care ◽  
Treatment Practices ◽  
Psychedelic Drugs ◽  
Treatment Paradigm ◽  
New Treatment ◽  
Definition Of ◽  
The Right ◽  
Psychological Integration

AbstractSerotonergic psychedelics such as psilocybin, lysergic acid diethylamide (LSD), or dimethyltryptamine (DMT), as well as psychoactive drugs that trigger phenomenologically- related experiences like 3,4-methylenedioxymethamphetamine (MDMA) and ketamine, belong to the most promising treatment approaches in contemporary psychiatry. Psychedelic-assisted psychotherapy is not only a new treatment paradigm in psychopharmacology, but it also requires a redefinition of psychotherapeutic processes and the contextualization of psychopharmacological interventions within a new treatment infrastructure. Crucial for future practice and research in the field are (1) informed patient referral and co-treatment practices, (2) screening (e. g., choosing the right patients for these therapies), (3) the dosing preparation sessions, (4) the assisted dosing sessions as well as after-care procedures such as (5) psychological integration and (6) supporting the development of structured patient communities. Definition of future treatment delivery infrastructures and requirements for therapist training are further challenges for research and practice. Finally, the implementation of psychedelic-assisted psychotherapy in routine mental health care must be embedded into public communication about the potential and risks of these innovative therapeutic approaches. This paper provides a synopsis of challenges for practitioners, researchers, and regulators to be addressed in the approval processes of psychedelics.

mCity

2007 ◽  
pp. 12-29
Author(s):  
Anette Hallin ◽  
Kristina Lundevall
Keyword(s):  
Health Care ◽  
Mobile Technology ◽  
Mobile Services ◽  
End Users ◽  
Sustainable Systems ◽  
Wide Range ◽  
Telecom Industry ◽  
User Friendly ◽  
The City ◽  
User Focus

This chapter presents the mCity Project, a project owned by the City of Stockholm, aiming at creating user-friendly mobile services in collaboration with businesses. Starting from the end-users’ perspective, mCity focuses on how to satisfy existing needs in the community, initiating test pilots within a wide range of areas, from health care and education, to tourism and business. The lesson learned is that user focus creates involvement among end users and leads to the development of sustainable systems that are actually used after they have been implemented. This is naturally vital input not only to municipalities and governments but also for the IT/telecom industry at large. Using the knowledge from mCity, the authors suggest a new, broader de?nition of “m-government” which focuses on mobile people rather than mobile technology.

Client Information Handout Reprinted from Pet Focus, with Permission

1991 ◽  
Vol 8 (2) ◽  
pp. 26-30 ◽  
Author(s):  
Kenneth F. Lyon
Keyword(s):  
Health Care ◽  
Dental Care ◽  
The Past ◽  
Treatment Techniques ◽  
Recent Developments ◽  
New Treatment

Today, it is recognized that our pets have dental problems that went unrecognized and untreated in the past. Recent developments in the field of veterinary dentistry, increased owner awareness, and new treatment techniques make dental care an indispensable part of pet health care. Routine preventative procedures such as brushing the teeth should be a regular aspect of the care we extend to our pets. J. Vet. Dent., 1991; 8(2): 26–30.

How personalized medical data could improve health care

2014 ◽  
Vol 67 ◽  
pp. 303-305
Author(s):  
Niklas Andersson ◽  
Alice Grinberg ◽  
Niels Okkels
Keyword(s):  
Health Care ◽  
Medical Data ◽  
Improve Health Care ◽  
Improve Health

scholarly journals CureCancer Digital Platform In The Routine Clinical Oncology Practice Facilitates Patients’ Self-Data Recording, Communicating With Health Care Professionals, Treatment Adherence And “Distancing Interventions” During Covid-19 And Reduces Costs. A Feasibility And Satisfaction Study*.

2021 ◽  
Author(s):  
Dimitra Galiti ◽  
Helena Linardou ◽  
Sofia Agelaki ◽  
Athanasios Karampeazis ◽  
Nikolaos Tsoukalas ◽  
...  
Keyword(s):  
Health Care ◽  
Treatment Adherence ◽  
Health Care Professionals ◽  
Health Care Policy ◽  
High School Graduates ◽  
Data Access ◽  
Routine Practice ◽  
Clinical Trial Results ◽  
Oncology Practice ◽  
User Friendly

Abstract Purpose: We assessed CureCancer’s feasibility and patients’ and HCPs’ satisfaction. CureCancer is a patient-centric/driven platform, which enables patients to self-create their profile, report symptoms and communicate with physicians.Methods: Patients from 18 Centers were asked to register at CureCancer, upload their data and complete a questionnaire on demographics, disease and treatment characteristics, and their satisfaction. Results: 159 patients were enrolled and 144 (90.6%) registered. 114 of 144 (79.1%), 63 males and 51 females, median age 54.5 years, completed the questionnaire. 64 patients were University and 35 were high School graduates. 46 patients had metastatic disease, 87 were on active treatment and 51 received supportive care. All patients also visited non-oncology HCPs. Nineteen patients changed work status and 49 had children below 24 years. Registration was “very/very much” easy for 98 (86.0 %) patients. File uploading was “very/very much” easy for 47 (41.2%) patients. Over 80% of patients and physicians preferred the digital way. 99 patients and all HCPs will recommend CureCancer to others. Easy data access, improved communication, feeling safe, treatment adherence, interventions from distance, particularly during covid-19 pandemic and saving time and money, were highly commented by patients and HCPs. Conclusion: CureCancer was feasible and patients and HCPs were satisfied. File uploading changed to become more user friendly. Integration of CureCancer in the routine practice is expected to improve cancer care and reduce cancer costs. Patients’ self-reporting, with CureCancer, can increase the accuracy of clinical trial results and map social/work/economic issues following cancer diagnosis to assist health care policy.

scholarly journals Machine learning based outlier detection for medical data

2021 ◽  
Vol 24 (1) ◽  
pp. 564
Author(s):  
R. Vijaya Kumar Reddy ◽  
Shaik Subhani ◽  
B. Srinivasa Rao ◽  
N. Lakshmipathi Anantha
Keyword(s):  
Machine Learning ◽  
Health Care ◽  
Outlier Detection ◽  
Health Care Industry ◽  
Work Load ◽  
Medical Data ◽  
The Novel ◽  
Cleaning Process ◽  
Care Industry ◽  
Global Data

<p>The concept of machine learning generate best results in health care data, it also reduce the work load of health care industry. This algorithm potentially overcome the issues and find out the novel knowledge for development of medical date in health care industry. In this paper propose a new algorithm for finding the outliers using different datasets. Considering that medical data are analytic of mutually health problems and an activity. The proposed algorithm is working based on supervised and unsupervised learning. This algorithm detects the outliers in medical data. The effectiveness of local and global data factor for outlier detection for medical data in real time. Whatever, the model used in this scenario from their training and testing of medical data. The cleaning process based on the complete attributes of dataset of similarity operations. Experiments are conducted in built in various medical datasets. The statistical outcome describe that the machine learning based outlier finding algorithm given that best accurateness.</p>

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