Artificial Intelligence in Cardiology: Applications and Obstacles

Effects of a lower limb walking exoskeleton on quality of life and activities of daily living in patients with complete spinal cord injury: A randomized controlled trial

BACKGROUND

In recent years, lower limb walking exoskeletons have been widely used in the study of spinal cord injury (SCI).

OBJECTIVE

To explore the effect of a lower limb walking exoskeleton on quality of life and functional independence in patients with motor complete SCI.

METHODS

This was a multi-center, single blind, randomized controlled trial. A total of 16 SCI patients were randomly assigned to either the exoskeleton-assisted walking (EAW) group (n= 8) or the conventional group (n= 8). Both groups received conventional rehabilitation training, including aerobic exercise and strength training. The EAW group additionally conducted the exoskeleton-assisted walking training using an AIDER powered robotic exoskeleton for 40-50 minutes, 5 times/week for 8 weeks. World Health Organization quality of life-BREF (WHOQOL-BREF) and the Spinal Cord Independence Measure III (SCIM-III) were used for assessment before and after training.

RESULTS

There was an increasing tendency of scores in the psychological health, physical health, and social relationships domain of WHOQOL-BREF in the EAW group after the intervention compared with the pre-intervention period, but there was no significant difference (P> 0.05). SCIM-III scores increased in both groups compared to pre-training, with only the conventional group showing a significant difference after 8 weeks of training (P< 0.05).

CONCLUSION

A lower limb walking exoskeleton may have potential benefits for quality of life and activities of daily living in patients with motor complete SCI.

The Role of Artificial Intelligence in Echocardiography: A Clinical Update

PURPOSE OF REVIEW

In echocardiography, there has been robust development of artificial intelligence (AI) tools for image recognition, automated measurements, image segmentation, and patient prognostication that has created a monumental shift in the study of AI and machine learning models. However, integrating these measurements into complex disease recognition and therapeutic interventions remains challenging. While the tools have been developed, there is a lack of evidence regarding implementing heterogeneous systems for guiding clinical decision-making and therapeutic action.

RECENT FINDINGS

Newer AI modalities have shown concrete positive data in terms of user-guided image acquisition and processing, precise determination of both basic and advanced quantitative echocardiographic features, and the potential to construct predictive models, all with the possibility of seamless integration into clinical decision support systems. AI in echocardiography is a powerful and ever-growing tool with the potential for revolutionary effects on the practice of cardiology. In this review article, we explore the growth of AI and its applications in echocardiography, along with clinical implications and the associated regulatory, legal, and ethical considerations.

Comment on: Smart Technologies Used as Smart Tools in the Management of Cardiovascular Disease and Their Future Perspective

With keen interest and seriousness, we have read the article "Smart Technologies used as Smart Tools in the Management of Cardiovascular Disease and their Future Perspective" by Muneeb Ullah et al. and writing to provide a critique. For its clarity and conciseness, we applaud the author for his extensive research on this delicate topic. The authors have concisely written several scenarios of using smart technologies used as smart tools in the management of cardiovascular disease, such as wearable devices, mobile applications,3D printing technologies, artificial intelligence, remote monitoring systems, and electronic health records. Nonetheless, While the study addresses an important topic in the field of cardiology, we believe there are certain aspects that require further consideration and exploration.