Due to the recent implementation of the Finnish well-being reform, there is limited research discussing the reform's aims and its alignment with existing Finnish patient portals. The objective of... Show More

Due to the recent implementation of the Finnish well-being reform, there is limited research discussing the reform's aims and its alignment with existing Finnish patient portals. The objective of this research is to assess the alignment between existing Finnish patient portals and the newly implemented well-being reform. This research is supported by the insights gained from monitoring the US health reform survey that was conducted in 2021. By Aligning patient portals with the well-being reform, there is an opportunity to achieve patient-centered care and facilitate improved communication between patients and healthcare providers.

The K-nearest neighbor interpolation method was used to fill in missing data of five indicators of coronary heart disease, diabetes, total cholesterol, triglycerides, and albumin;, and the SMOTE... Show More

The K-nearest neighbor interpolation method was used to fill in missing data of five indicators of coronary heart disease, diabetes, total cholesterol, triglycerides, and albumin;, and the SMOTE algorithm was used to balance the number of variable indicators. The Relief-F algorithm was used to remove 18 variable indicators and retain 42 variable indicators. LASSO and ridge regression algorithms were used to remove eight variable indicators and retain 52 variable indicators; The prediction accuracy, recall, and AUC values of the linear kernel support vector machine model filtered using Relief-F and LASSO features are high, and the prediction results are optimal; The test result of random forest screened by Relief-F and LASSO features is better than that of the support vector machine model. It is concluded that the random forest model screened by Relief-F features is better as a prediction of lung cancer typing. The research results provide theoretical data support for predicting lung cancer classification using machine learning methods.

Cardiovascular disease (CVD) is a variety of diseases that affect the blood vessels and the heart. The authors propose a set of deep learning inspired by the approach used in CVD support centers for... Show More

Cardiovascular disease (CVD) is a variety of diseases that affect the blood vessels and the heart. The authors propose a set of deep learning inspired by the approach used in CVD support centers for the early diagnosis of CVD using deep learning techniques. Data were collected from patients who received CVD screening. The authors propose a prediction model to diagnose whether people have CVD or not and to provide awareness or diagnosis on that. The performance of each algorithm is compared with that of long-, short-time memory, feedforward, and cascade forward neural networks, and Elman neural networks. The results show that the ensemble deep learning classification and prediction model achieved 98.45% accuracy. Using the proposed early diagnosis model for CVD can help simplify the diagnosis of CVD by medical professionals.

As a favorite sport of teachers and students, long-distance running can enhance physical fitness. However, due to nonstandard movements in sports, teachers and students get injured psysically.... Show More

As a favorite sport of teachers and students, long-distance running can enhance physical fitness. However, due to nonstandard movements in sports, teachers and students get injured psysically. Taking the prevention of long-distance running injuries of teachers and students in colleges and universities as the research goal, this article investigates the teachers and students of a physical education college in Shanxi Province by means of questionnaire survey, counts the functional indexes of teachers and students in long-distance running for one year and analyzes the injuries. The results show that the injury rate of teachers and students is 45.5%; Teachers and students with only one injury are the most, and knee injuries are the most common, with a mild injury rate of 60.98% and concentrated in November-December and June-July. The main reasons for the injuries of teachers and students are poor physical fitness, insufficient warm-up, and poor sports equipment. Through full warm-up exercise and adequate rest, common injuries in long-distance running can be effectively prevented.

The number of people in the US with opioid abuse exceeds two million, and the total cost is approximately $100B per year. There is a need for smart interventions that can lead to better outcomes for... Show More

The number of people in the US with opioid abuse exceeds two million, and the total cost is approximately $100B per year. There is a need for smart interventions that can lead to better outcomes for patients and reduce the need for healthcare resources. In this study, the authors present three smart interventions for patients: (a) mobile reminders, (b) electronic monitoring, and (c) composite intervention. More specifically, the authors present a design approach for smart interventions and operationalize the interventions. They have developed an analytical model for evaluating interventions. Interventions are cost-effective for higher values of intervention effectiveness, hospital, and emergency room cost. However, with quality-of-life (QoL) improvement, cost-effectiveness improves significantly. The authors also explored the use of financial incentives for increasing the adoption of interventions. These results will help patients, healthcare professionals, decision-makers, and family members to choose the most suitable intervention to address opioid abuse.

The objective is to explore the etiology, diagnosis, treatment, and prevention of children's knee joint sports injury. The medical records of hospitalized children with sports injuries from 2019 to... Show More

The objective is to explore the etiology, diagnosis, treatment, and prevention of children's knee joint sports injury. The medical records of hospitalized children with sports injuries from 2019 to 2021 were retrospectively analyzed. The total number of hospitalized children with knee joint sports injury increased from 27 in 2019 to 46 in 2021. The main diseases are meniscus injury, dislocation of patella, avulsion fracture of tibial intercondylar crest, ligament injury, articular cartilage injury, and other diseases. Children's sports injuries occur in different ages groups, with the highest incidence in the age group of 7-14, and the incidence rate of boys is about 1.5 times that of girls. Moreover, the number of knee joint sports injury diseases in children is increasing, especially for school-age children. Low energy injury is the most common cause of injury, but high energy injury may lead to serious knee joint function damage, which should be paid great attention.

China is currently one of the countries with the largest elderly population in the world, and the issue of population aging has become a widespread concern. The behavior recognition algorithm based... Show More

China is currently one of the countries with the largest elderly population in the world, and the issue of population aging has become a widespread concern. The behavior recognition algorithm based on deep learning is currently the main behavior recognition algorithm and one of the basic technologies in the field of computer vision. In existing research, the method of constructing complex classification models based on manual feature representation can no longer meet the requirements of high recognition accuracy and applicability, and the introduction of deep learning has brought new development directions for behavior recognition. Therefore, this article aims to study how to apply deep learning-based behavior recognition technology more accurately and effectively in the care of elderly people in the context of “artificial intelligence.”

The current problem of providing for the aged in China is extremely serious. As a weak member of society, the basic right of the elderly is the harmonious and stable development of society... Show More

The current problem of providing for the aged in China is extremely serious. As a weak member of society, the basic right of the elderly is the harmonious and stable development of society, especially in China, where the problem of aging is extremely severe, and the general pension institutions cannot fully and meticulously meet the precise needs of different elderly people. Therefore, this paper mainly studies the intelligent nursing system for the elderly based on big data, aiming to meet the requirements of the elderly of different ages for the elderly through the combination of big data and old-age care. This old-age care model is based on the usual application environment, the internet “big data” as the foundation, accurately applying intelligent technology to provide nursing services for the elderly, and providing interconnected, intelligent, convenient, and efficient old-age care services for the elderly, thus building a real-time, safe, convenient, and low-cost old-age care mechanism.

Using the convenient sampling method, the control group and the observation group were established. The control group was given a routine nursing scheme, while the observation group was given... Show More

Using the convenient sampling method, the control group and the observation group were established. The control group was given a routine nursing scheme, while the observation group was given rehabilitation nursing scheme. The difference of curative effect between the two groups were compared and the results were analyzed and summarized. Results of the quality of life scores of patients in the two groups were compared. The results showed that the quality of life score of the patients in the observation group were higher than that of the control group (P<0.05); the satisfaction scores of patients was also compared. The results showed that the satisfaction scores of patients in the experimental group were significantly higher than that in the control group (P<0.05), so the patients in the observation group are better than the control group. The rehabilitation nursing scheme has a certain effect on the rehabilitation of knee ligament injury of printing workers.

This article examined the management of electronic health records in virtual health environments using rocket health as a case study. The specific objectives of the study were to determine the... Show More

This article examined the management of electronic health records in virtual health environments using rocket health as a case study. The specific objectives of the study were to determine the healthcare services provided at rocket health; examine the electronic health records management practices adhered to at rocket health; and determine the inhibitors to effective electronic health records management at rocket health. A case study with a mixed-methods research approach was used. Data was collected using questionnaires, document reviews and structured interviews. The study finds that rocket health provided a range of healthcare services encompassing telehealth, pharmacy, last mile delivery, and an online store. These services predominantly operated in a digital format, resulting in the generation of electronic health records (EHRs), and therefore to capture and maintain these EHRs from multiple service points, rocket health implemented a cloud-based system.

In this article, the outpatient volume, hospitalization income and drug demand in hospital management are taken as the research objects, and a neural network combined prediction model is established... Show More

In this article, the outpatient volume, hospitalization income and drug demand in hospital management are taken as the research objects, and a neural network combined prediction model is established to predict the outpatient volume with the fitting prediction results of cubic polynomial regression model and grey model as the input of the network and the actual statistical outpatient volume as the output. Lasso variable selection method is used to determine the main indexes affecting the income of inpatients in hospital, and a prediction model combining grey prediction and artificial neural network is established to predict the income of inpatients in hospital. By studying the key characteristics of hospital drug demand, BP neural network, RBF neural network and GRNN generalized regression neural network are selected to predict the drug demand. By solving the quadratic programming problem and according to the weight rules, a combination forecasting model based on neural network is established to predict the drug demand, and the accuracy and stability of the model are evaluated.