Digital transformation has revolutionized various industries, especially the healthcare sector. It has made healthcare more inclusive by improving a wide range of outcomes from the prevention and treatment of disease to nursing care. Rapid technological changes in the healthcare sector are driving massive improvements and innovations by aiding a wide range of digitized health promotion practices. Some of these practices are voluntarily undertaken by people interested in improving their health and fitness, but many others are employed in the interests of organizations and agencies.
The digital healthcare ecosystem is working on creating possibilities in several areas like home-based patient recovery, post-treatment care, and management of chronic illnesses. Some of the key areas in which healthcare has been showing major transformation are electronic health records, telemedicine, and wearable technology. Other fundamental areas in which healthcare has evolved in today’s digitized era are big data and artificial intelligence. The healthcare industry has access to vast amounts of data that can be used to identify trends and patterns in patient health that can be used to develop more effective treatments. Additionally, artificial intelligence is playing a vital role in everything from automating monotonous and routine tasks in medical practice to managing patients and medical resources.
Growing applications of deep learning in healthcare
Deep learning is a subset of machine learning that trains artificial neural networks to recognize patterns in large data sets. It has several potential applications in healthcare and is transforming patient care by playing a fundamental role for health systems in clinical practice. Below mentioned are some of the most promising implementations:
Medical imaging: By training neural networks to recognize patterns in medical images, such as X- rays, CT scans, and MRI scans, deep learning algorithms can help doctors to identify and diagnose diseases at an early stage.
Drug discovery: To analyze large sets of chemical compounds and predict their potential efficacy in treating diseases, deep learning plays a very important role. This can accelerate the drug discovery process, allowing researchers to identify promising drug candidates more quickly.
Disease surveillance: Deep learning plays a key role in tracking the spread of infectious diseases by analyzing large sets of data, such as social media posts and news articles. By identifying patterns and trends in this data, deep learning algorithms can help public health officials to detect outbreaks early and take actions accordingly.
Genome analysis: Deep learning has a promising future in the field of genomics. Complex Neural Networks (CNNs) are useful in analyzing and understanding complex biological data.
Insurance fraud: With the use of deep learning models, it is easy to predict the future trends and actions for proposing smart insurance to customers. It also helps in analyzing medical insurance fraud claims.
Aiding quality healthcare with the use of healthcare and medical interactive apps
The current landscape of healthcare has been revolutionized a lot and healthcare and medical interactive apps are playing a pivotal role in improving the quality of healthcare services. Some of the benefits of medical interactive applications include the following:
Easy accessibility and personalization: Healthcare and medical interactive apps can provide easy and personalized and quality medical assistance and quick access to medical information, health advice, and healthcare services. These apps can also provide personalized health advice and with the help of these apps, patients can receive medical assistance at one’s convenience.
Improved healthcare outcomes and increased patient engagement: Healthcare and medical interactive apps can improve healthcare outcomes by promoting disease prevention, early detection, and timely intervention. It can also improve patient engagement and encourage patients to take an active role in their own healthcare journey.
Cost-effective care: Patients can receive medical assistance at a lower cost, without compromising on the quality of care with the use of healthcare and medical interactive apps. This is undoubtedly a cost-effective alternative as compared to traditional medical care.
Challenges in the implementation journey and opportunities ahead
There are several challenges to digitalization of healthcare like interoperability, cybersecurity, privacy, and challenging misinformation. All these challenges can be resolved with adequate strategy and resources by cross leveraging the adaptations and solutions from industries where technology is at the forefront. The four important facets to provide digital health solutions are:
Smart healthcare systems to improve precision in diagnostics and therapeutic devices
Smart connect devices to remote devices monitoring and predictive maintenance
Connected consumer for preventive healthcare applications
Smart remote care for remote patient monitoring and home care
Integrating these and its deployment and maintenance with a multilateral approach is key to a successful implementation of a digital strategy in healthcare. While implementing these technologies we need to also make sure that there is a focus on the more human-centered digital environment so that there is a reduced clinician burnout as well. This will not only lead to better health outcomes but also efficient healthcare processes.
