Brain Tumors Presumed Malignant without Biopsy-Evaluation and Treatment Problems

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Ioana Soare ◽  
◽  
Petru-Emil Muntean ◽  
Roxana Mirica ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Brain Tumors ◽  
Disability Pension ◽  
Palliative Treatment ◽  
Treatment Protocol ◽  
Assistive Technologies ◽  
Insurance Companies ◽  
Short Term ◽  
Oncological Treatment ◽  
Health Insurance Companies

Patients with brain tumors may have the following issues: tumors are in deep or vital regions; they refuse the biopsy; the neurosurgeon does not reach the tumoral tissue and the biopsy is irrelevant; advanced cases, considered “outside the surgical and oncological therapeutic resources”. These patients cannot receive oncological treatment or radiotherapy because of the restrictive indications of the insurers (health insurance companies) or because of the risk of allegations of malpractice. Patients will not receive some social security rights (short term sick leave, disability pension) in the same way as cancer patients, but only as a patient with a common illness. Patients can receive palliative treatment, can be hospitalized in oncology departments. We propose to discuss a separate diagnostic and treatment protocol for this group of patients, based on laboratory (ctDNA) and imagistic criteria. Assistive technologies using Computer Vision Model combined with Convolutional Neural Network may help classificate and diagnose these tumors.

scholarly journals An Empirical Study on the Equity Performance of China's Health Insurance Companies During the COVID-19 Pandemic—Based on Cases of Dominant Listed Companies

2021 ◽  
Vol 9 ◽  
Author(s):  
Rendao Ye ◽  
Na An ◽  
Yichen Xie ◽  
Kun Luo ◽  
Ya Lin
Keyword(s):  
Neural Network ◽  
Health Insurance ◽  
Stock Price ◽  
Short Term Memory ◽  
Insurance Industry ◽  
Back Propagation ◽  
Listed Companies ◽  
Insurance Companies ◽  
Neural Network Models ◽  
Health Insurance Companies

The health insurance industry in China is undergoing great shocks and profound impacts induced by the worldwide COVID-19 pandemic. Taking for instance the three dominant listed companies, namely, China Life Insurance, Ping An Insurance, and Pacific Insurance, this paper investigates the equity performances of China's health insurance companies during the pandemic. We firstly construct a stock price forecasting methodology using the autoregressive integrated moving average, back propagation neural network, and long short-term memory (LSTM) neural network models. We then empirically study the stock price performances of the three listed companies and find out that the LSTM model does better than the other two based on the criteria of mean absolute error and mean square error. Finally, the above-mentioned models are used to predict the stock price performances of the three companies.

Online Patient Consultation

2020 ◽  
Vol 158 (04) ◽  
pp. 345-350
Author(s):  
Christian Juhra ◽  
Jörg Ansorg ◽  
David Alexander Back ◽  
Dominik John ◽  
Andrea Kuckuck-Winkelmann ◽  
...  
Keyword(s):  
New Technologies ◽  
Communication Technologies ◽  
Phone Call ◽  
Insurance Companies ◽  
Personal Contact ◽  
Software Products ◽  
Patient Consent ◽  
Health Insurance Companies ◽  
Patient Consultation ◽  
Certified Software

AbstractNew communication technologies allow patients to communicate with their physicians from anywhere using computer or smartphone. Adding video to the mere phone call optimizes the personal contact between patient and physicians regardless of distance. Legal and reimbursements requirements must be taken into account, especially only certified software products must be used. In addition, patient consent is needed and confidentiality must be assured. The video patient consultation can be reimbursed by the health insurance companies. As with all new technologies, the introduction of these video consultations faced some challenges. Although patients and physicians have expressed great interest in this technology, it has been rarely used so far. The current COVID crisis increased the need for video consultations resulting in an increasing use of video patient consultation. It can be expected that this demand will still exists after the COVID crisis.

scholarly journals Electricity Consumption Forecasting Based on a Bidirectional Long-Short-Term Memory Artificial Neural Network

2020 ◽  
Vol 13 (1) ◽  
pp. 104
Author(s):  
Dana-Mihaela Petroșanu ◽  
Alexandru Pîrjan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Short Term Memory ◽  
Electricity Consumption ◽  
Short Term ◽  
Term Memory ◽  
Storage Room ◽  
Long Short Term Memory ◽  
Commercial Center ◽  
Business And Management

The accurate forecasting of the hourly month-ahead electricity consumption represents a very important aspect for non-household electricity consumers and system operators, and at the same time represents a key factor in what regards energy efficiency and achieving sustainable economic, business, and management operations. In this context, we have devised, developed, and validated within the paper an hourly month ahead electricity consumption forecasting method. This method is based on a bidirectional long-short-term memory (BiLSTM) artificial neural network (ANN) enhanced with a multiple simultaneously decreasing delays approach coupled with function fitting neural networks (FITNETs). The developed method targets the hourly month-ahead total electricity consumption at the level of a commercial center-type consumer and for the hourly month ahead consumption of its refrigerator storage room. The developed approach offers excellent forecasting results, highlighted by the validation stage’s results along with the registered performance metrics, namely 0.0495 for the root mean square error (RMSE) performance metric for the total hourly month-ahead electricity consumption and 0.0284 for the refrigerator storage room. We aimed for and managed to attain an hourly month-ahead consumed electricity prediction without experiencing a significant drop in the forecasting accuracy that usually tends to occur after the first two weeks, therefore achieving a reliable method that satisfies the contractor’s needs, being able to enhance his/her activity from the economic, business, and management perspectives. Even if the devised, developed, and validated forecasting solution for the hourly consumption targets a commercial center-type consumer, based on its accuracy, this solution can also represent a useful tool for other non-household electricity consumers due to its generalization capability.

scholarly journals Which health-related reasons lead to prehospital emergency care and how does subjective emergency status connect to subsequent care?

2021 ◽  
Author(s):  
Silke Piedmont ◽  
Anna Katharina Reinhold ◽  
Jens-Oliver Bock ◽  
Enno Swart ◽  
Bernt-Peter Robra
Keyword(s):  
Health Insurance ◽  
Emergency Care ◽  
Third Party ◽  
Insurance Companies ◽  
Prehospital Emergency Care ◽  
Health Related ◽  
Life Threatening ◽  
Prehospital Emergency ◽  
Health Insurance Companies ◽  
Reported Data

Abstract Objectives/Background In many countries, the use of emergency medical services (EMS) increases steadily each year. At the same time, the percentage of life-threatening complaints decreases. To redesign the system, an assessment and consideration of the patients’ perspectives is helpful. Methods We conducted a paper-based survey of German EMS patients who had at least one case of prehospital emergency care in 2016. Four health insurance companies sent out the questionnaire to 1312 insured persons. We linked the self-reported data of 254 respondents to corresponding claims data provided by their health insurance companies. The analysis focuses a.) how strongly patients tend to call EMS for themselves and others given different health-related scenarios, b.) self-perceived health complaints in their own index case of prehospital emergency care and c.) subjective emergency status in combination with so-called “objective” characteristics of subsequent EMS and inpatient care. We report principal diagnoses of (1) respondents, (2) 57,240 EMS users who are not part of the survey and (3) all 20,063,689 inpatients in German hospitals. Diagnoses for group 1 and 2 only cover the inpatient stay that started on the day of the last EMS use in 2016. Results According to the survey, the threshold to call an ambulance is lower for someone else than for oneself. In 89% of all cases during their own EMS use, a third party called the ambulance. The most common, self-reported complaints were pain (38%), problems with heart and circulation (32%), and loss of consciousness (17%). The majority of respondents indicated that their EMS use was due to an emergency (89%). We could detect no or only weak associations between patients’ subjective urgency and different items for objective care. Conclusion Dispatchers can possibly optimize or reduce the disposition of EMS staff and vehicles if they spoke directly to the patients more often. Nonetheless, there is need for further research on how strongly the patients’ perceived urgency may affect the disposition, rapidness of the service and transport targets.

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