Health Care Science

The way medical professionals diagnose, treat, and manage diseases has changed dramatically due to several innovative technologies that have emerged in recent years. Thanks to sophisticated algorithms that examine enormous volumes of patient data to find patterns and predict outcomes, artificial intelligence (AI) and machine learning (ML) have become increasingly potent instruments that enable more precise diagnoses. Telemedicine has increased access to healthcare, particularly in rural regions, by facilitating remote monitoring and consultations. Furthermore, wearable technology and IoMT have enabled people to track their health parameters in real-time, offering insightful information to patients and healthcare professionals. Moreover, personalized therapies have become possible thanks to genomics and personalized medicine developments, which use a patient's genetic information to create exact medications. Together, these technologies have improved healthcare delivery systems’ efficiency and patient-centeredness while raising the standard of care.

Surveyed from June 20 to August 31, 2023, across 150 cities and various urban–rural settings in China, our study employed stratified sampling to gather comprehensive data on Chinese residents' psychology and behavior. Trained surveyors conducted face-to-face interviews, covering health, family, social environment, psychological conditions, and behavioral patterns. Quality control ensured robust data for informing health policies and services.

We proposed a novel approach that incorporates the lung + space as a constraint during deep learning model training for pneumothorax segmentation on 2D chest radiographs. We utilized external datasets and an auxiliary task of lung segmentation to generate a specific constraint of lung + space for each chest radiograph, circumventing the need for additional annotations. We incorporated a discriminator to eliminate unreliable constraints caused by the domain shift between the auxiliary and target datasets. Our results demonstrated consistent improvements across six baseline models built on three segmentation architectures and two convolutional neural networks backbones.

Our findings revealed that nearly 38% of Indian households with diabetic members experienced catastrophic health expenditure (at 10% threshold) and around 10% of DM-affected households fell below the poverty line due to OOPE, regardless of the type of care sought. 48.5% of households used distressed sources to finance the inpatient costs of DM. Of all the individuals who reported having DM during the last 15 days prior to the survey date, 0.8% did not seek treatment.

China has the biggest medical insurance program in the world with coverage of 95% population, with tremendous pressure on cost control. Since 2015, China's healthcare ecosystem has been reshaped by the rising China innovation, driven by regulatory reform, enhancement of R&D capability, and capital market development. How to balance affordability and innovation will be critical for China to continue the trajectory.

The way medical professionals diagnose, treat, and manage diseases has changed dramatically due to several innovative technologies that have emerged in recent years. Thanks to sophisticated algorithms that examine enormous volumes of patient data to find patterns and predict outcomes, artificial intelligence (AI) and machine learning (ML) have become increasingly potent instruments that enable more precise diagnoses. Telemedicine has increased access to healthcare, particularly in rural regions, by facilitating remote monitoring and consultations. Furthermore, wearable technology and IoMT have enabled people to track their health parameters in real-time, offering insightful information to patients and healthcare professionals. Moreover, personalized therapies have become possible thanks to genomics and personalized medicine developments, which use a patient's genetic information to create exact medications. Together, these technologies have improved healthcare delivery systems’ efficiency and patient-centeredness while raising the standard of care.

Surveyed from June 20 to August 31, 2023, across 150 cities and various urban–rural settings in China, our study employed stratified sampling to gather comprehensive data on Chinese residents' psychology and behavior. Trained surveyors conducted face-to-face interviews, covering health, family, social environment, psychological conditions, and behavioral patterns. Quality control ensured robust data for informing health policies and services.

It synthesizes evidence on various components of transitional care. The need for multifaceted interventions required to improve long-term outcomes. Identifies the role of each healthcare professional and the integration of different interventions. Integrative healthcare programs facilitate continuity and care coordination post-discharge after acute myocardial infarction.

Our findings revealed that nearly 38% of Indian households with diabetic members experienced catastrophic health expenditure (at 10% threshold) and around 10% of DM-affected households fell below the poverty line due to OOPE, regardless of the type of care sought. 48.5% of households used distressed sources to finance the inpatient costs of DM. Of all the individuals who reported having DM during the last 15 days prior to the survey date, 0.8% did not seek treatment.