Current Issue : October - December Volume : 2020 Issue Number : 4 Articles : 5 Articles
Cardiovascular disease (CVD), despite the significant advances in the diagnosis and treatments, still represents the leading cause\nof morbidity and mortality worldwide. In order to improve and optimize CVD outcomes, artificial intelligence techniques have\nthe potential to radically change the way we practice cardiology, especially in imaging, offering us novel tools to interpret data and\nmake clinical decisions. AI techniques such as machine learning and deep learning can also improve medical knowledge due to the\nincrease of the volume and complexity of the data, unlocking clinically relevant information. Likewise, the use of emerging\ncommunication and information technologies is becoming pivotal to create a pervasive healthcare service through which elderly\nand chronic disease patients can receive medical care at their home, reducing hospitalizations and improving quality of life. The\naim of this review is to describe the contemporary state of artificial intelligence and digital health applied to cardiovascular\nmedicine as well as to provide physicians with their potential not only in cardiac imaging but most of all in clinical practice....
Telehealth, as an indispensable means of technical support in the Healthy China Strategy, currently has less than 20 percent\nadoption rate in China despite a great deal of government policies and investments. In the current study, to analyse the influencing\nfactors behind doctorsâ?? and patientsâ?? adoption of telehealth, an asymmetric dynamic evolutionary game model of doctor-patient\nbehaviour selection was established. Based on the model solution, the evolutionarily stable strategies that emerge in different\nsituations were analysed. The results show that it is difficult for the adoption of telehealth in China to keep pace with coverage due\nto the â??dual lowâ? nature of telehealth: both doctorsâ?? utility from telehealth and patientsâ?? telehealth cost threshold are too low to\nincentivize adoption. The strategy to promote the adoption of telehealth in China should include providing adequate training for\ndoctors and patients on the use of telehealth technology, rewarding doctors who provide telehealth services and raising the\nthreshold cost of patientâ??s telehealth adoption....
In response to the COVID-19 pandemic, health care modalities such as video consultations\nhave been rapidly developed to provide safe health care and to minimize the risk of spread.\nThe purpose of our study is to explore Spanish healthcare professionalsâ?? perceptions about\nthe implementation of video consultations. Based on the testimonies of 53 professionals,\ndifferent categories emerged related to the four identified themes: benefits of video consultations\n(for professionals, patients, and the health system, and compared to phone calls), negative aspects\n(inherent to new technologies and the risk of a perceived distancing from the professional), difficulties\nassociated with the implementation of video consultations (technological difficulties, lack of technical\nskills and refusal to use video consultation among professionals and patients), and the need for\ntraining (technological, nontechnical, and social-emotional skills, and adaptation of technical skills).\nAdditionally, the interviewees indicated that this new modality of health care may be extended to a\nbroader variety of patients and clinical settings. Therefore, since video consultations are becoming\nmore widespread, it would be advisable for health policies and systems to support this modality\nof health care, promoting their implementation and guaranteeing their operability, equal access\nand quality....
Malaria is a contagious disease that affects millions of lives every year. Traditional diagnosis of malaria in laboratory requires an\nexperienced person and careful inspection to discriminate healthy and infected red blood cells (RBCs). It is also very timeconsuming\nand may produce inaccurate reports due to human errors. Cognitive computing and deep learning algorithms simulate\nhuman intelligence to make better human decisions in applications like sentiment analysis, speech recognition, face detection,\ndisease detection, and prediction. Due to the advancement of cognitive computing and machine learning techniques, they are now\nwidely used to detect and predict early disease symptoms in healthcare field. With the early prediction results, healthcare\nprofessionals can provide better decisions for patient diagnosis and treatment. Machine learning algorithms also aid the humans to\nprocess huge and complex medical datasets and then analyze them into clinical insights. This paper looks for leveraging deep\nlearning algorithms for detecting a deadly disease, malaria, for mobile healthcare solution of patients building an effective mobile\nsystem. The objective of this paper is to show how deep learning architecture such as convolutional neural network (CNN) which\ncan be useful in real-time malaria detection effectively and accurately from input images and to reduce manual labor with a mobile\napplication. To this end, we evaluate the performance of a custom CNN model using a cyclical stochastic gradient descent (SGD)\noptimizer with an automatic learning rate finder and obtain an accuracy of 97.30% in classifying healthy and infected cell images\nwith a high degree of precision and sensitivity. This outcome of the paper will facilitate microscopy diagnosis of malaria to a\nmobile application so that reliability of the treatment and lack of medical expertise can be solved....
The COVID-19 pandemic forced physicians to quickly adapt and find ways to provide their\nusual offline services by using online tools. We aimed to understand how physicians adapted to\nthe sudden need for telehealth and if their perception of telehealth changed due to their experience\nduring the COVID-19 pandemic. We conducted an exploratory sequential mixed-methods study.\nWe interviewed five Lebanese physicians and thematically analyzed the interviews. We developed\na questionnaire based on the analysis results and administered it online to physicians in Lebanon.\nIn total, 140 responses were collected. We found that, during the COVID-19 pandemic, physicians\nengaged in more telehealth activities in the realms of telemedicine, public awareness, continuing\nmedical education, research, administration, and teaching. They also expanded their repertoire of\ninformation-technology tools. Our results also show that there was a significant shift in the physiciansâ??\nperceptions, indicating greater openness and willingness to adopt telehealth services. However,\na significant amount of skepticism and uncertainty regarding telemedicine remains, especially\nconcerning its efficiency, safety, and the adequacy of existing regulations. Based on our findings,\nwe offer recommendations for health IT policy makers, developers, and researchers, to sustain the\ncontinuity of telehealth activities beyond the COVID-19 pandemic....
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