The ways by which emerging technology transforms the health industry

Introduction

Nowadays, technology drives many sectors, including healthcare. It keeps transforming the health industry through various innovations. The technological innovations keep finding better options to prevent and cure diseases. Artificial Intelligence (AI) has helped with the boom of technological innovation in healthcare through the digitization of healthcare workflows. It is essential to remain mindful of the latest trends in the healthcare industry. The technology focuses on improving performance, efficiency, productivity, and security without sacrificing accessibility and reliability.

Artificial Intelligence

Mental-Health Assessment

AI models get used to diagnose and analyze the mental health of people and provide ways to help through proper counseling and other therapeutic techniques in the healthcare sector. Messages from social media platforms got analyzed for suicidal tendencies, toxic loneliness, and depression using AI models. These helped in providing the right treatment to those people who struggle with these mental health issues. The AI gets used to understand the nuances of brain function like chemical changes in human and animal brains that reveal the symptoms of any kind of disease from skin to genetic level. Artificial Intelligence tools can be used to identify Alzheimer’s and Parkinson’s disease, and Autism from an early stage, which is helpful in proper diagnosis and treatment of the same. The advances in deep learning and AI audio processing can help analyze human speech to identify the early onset of Dementia.

Disease Diagnosis and Drug Development

With AI, innovative technology is getting used in healthcare to facilitate precise disease diagnosis and drug development. AI tools improve the efficiency of information processing and decision making. Machine Language gets used to design and develop new pharmaceuticals.

Recently to diagnose and treat for COVID-19 effects, Project InnerEye, a radioactive AI tool got developed by Microsoft that sped up the 3D contouring of the patient. It drastically reduced the diagnosis time from minutes to hours.

Cancer Diagnosis

Microsoft developed Project Hanover, an AI tool, to catalog biomedical research papers that reduce the time to diagnose Cancer while assisting with which drugs should be used for each patient. The biopsy for cancer focuses on tissue extraction and its analysis, which has been the main means of reliable diagnostics before AI tools came along. Histopathology relies on digital scans of a specific area affected by cell mutations, which gets examined by pathologists using Whole Slide Images (WSI). Working with WSI is challenging due to the image resolutions. The informative WSI scans take a lot of analyzing time to understand all its nuances. In come AI tools that simplify the process of analyzing WSI through computer vision and Convolutional Neural Networks (CNN). It brings high-quality results in much reduced time-frames with just a little preparation for model training.

Natural Language Processing (NLP)

As a revolution for AI in healthcare, UCLA researchers combined chatbot technologies with AI systems to create a Virtual Interventional Radiologist (VIR). It helps patients to self-diagnose while assisting doctors to diagnose these patients. The NLP technology of AI gets used by AI tools to assist in the disease-diagnosis of patients. The chatbots obtain proper and precise information from patients with which the right treatments can begin.

Telemedicine: The Evolution of Remote Care

Cloud Hosting with Data Storage

The data of a lot of patients need to be stored in the cloud, which is compliant with the government regulations on protected health information. These regulations are critical to maintain functionality and efficiency for any healthcare operation that requires Electronic Health Records (EHR). The teleconferencing and data hosting details features are useful to all healthcare organizations along with location services, appointment management, secure messaging, security, visit history, healthcare provider reviews, and wearable integration. Some of the other data for telemedicine and remote care through AI tools include storage of fitness data from consumer service devices like Google Fit, and Apple HealthKit. Proper maintenance of integration securely and efficiently benefits the patient and caregiver within the healthcare system.

Extended Reality in Healthcare

Augmented Reality and Mixed Reality

The healthcare organizations get benefits from Augmented Reality (AR) and Mixed Reality (MR) settings. For instance, the MR headsets like Microsoft Hololens 2 used by surgeons provide heads-up information while allowing them to use both their hands during an operation procedure. The head-mounted camera view of MR headsets enables doctors to observe the surgery and offer advice if needed. AR headsets get used for similar applications. The AI technology aids nurses to find veins to draw blood from.

Metaverse

Virtual Reality (VR) gets used in healthcare for training the AI tools. The virtual training sessions provided to doctors get used to improve their skills while preparing for a surgery. Through Metaverse and VR, therapeutic techniques get used to treat phobias like PTSD and fear of heights.

IoT and Wearables

IoT and wearables get involved in AI technology, and their potential in the healthcare industry is high. Healthcare organizations use IoT devices and wearables and these are increasingly becoming more connected for facilitating better provision of health to all patients.

Wearables and Smart Pills

Through wearables, doctors and nurses can monitor patients throughout the day remotely. The patients can self-monitor their health status through wearables as well. For instance, Smartwatches are great wearables that constantly monitor the health data and transmit the same to individuals. The heart-rate of patients gets monitored through these Smartwatches. These wearables have the technology to monitor blood-oxygen saturation along with physical health using pedometers. Low blood-oxygen saturation gets identified by Smartwatches with ease and it saves lives through this information. Photoplethysmography (PPG), an optical technology that measures blood-volume and blood-composition variations can be used through wearables like Smartwatches. Other wearables include bio-patches and Smart-Hearing-Aids. AI technology gets used to improve noise isolation of hearing aids.

The Smart-Pills transform IoT technology into the Internet of Bodies (IoB). These are edible electronics that work and serve as oral-medicines while providing doctors and nurses with valuable information about patients.

Organ Care Technology and Bio-Printing

Organ transplants are a must-have in today’s world and AI technology helps out with that using organ care technology and bio-printing. Organ care technology gets improved by extending the time for evaluating the condition of an organ and its transport. The Organ Care System takes care of organs outside the human body for several hours through proper care, heat, and provision of important and essential nutrients. The future of this technology is dependent on Artificial Intelligence to automatically take action without the intervention of doctors to preserve organs for longer time-frames. Machine Learning can be used to determine if an organ is being preserved the right way and is suitable for transplantation or not. The AI technology makes the whole process of organ preservation and increases the transplant feasibility faster.

Bio-Printing: Designing and Creating New Organs with the Mold of human-organs

In today’s world, organ preservation is a must as it is needed for transplantation. In addition to preserving organs alive outside of the body, other options need to be explored. Artificial Intelligence tools and some innovative technology help in devising other options through 3D printing of organs with the mold of existing human organs. It is a very real and developing technology that has moved on to clinical testing by now. Some of the body parts successfully 3D-printed or bio-printed include ears, corneas, bones, and skin. Here, first, a digital model of the organ tissue to be printed gets created. Careful attention is needed while creating the resolution and matrix structure. The Bio-Ink or living cells get used to create the organ-mold, which gets printed using Bio-Printing. After the organ gets printed, it gets tested for its functionality, which gets done through stimulation. Organ rejection gets prevented through the use of cells from patients that require organ transplantation. These cells get grown in a culture and then cultivated into the Bio-Ink necessary for printing. Although Bio-Printing has been done before, healthcare organizations are reluctant to use it in full capacity. Through AI analysis of organs and of recipient patient characteristics, the organs get better engineered to be compatible with hosts.

Future of Healthcare Technology

In the coming year, healthcare technology and organizations will continue to improve in every area possible through AI tools and innovative technologies. Proper security improves the facilitation of healthcare in a much needed way through the elimination of any threats that come along; the prevention process gets used as part of the proper response. Here, the quality and efficiency of care keep improving due to groundbreaking and evolving technologies like Artificial Intelligence, Augmented Reality, Virtual Reality, and Mixed Reality tools, and techniques like Bio-Printing along with Machine Learning. When deciding how to digitize, automate, and modernize the healthcare sector and organizations, time and funding are both on the line. So, it is necessary to team up with the right team of software engineers that understand the nuances of the required needs and objectives.

Conclusion

The above mentioned factors give a clear picture of how emerging technologies transform the health industry by driving it in the right direction. The AI tools simplify a lot of challenges faced by the healthcare industry through proper transformation of processes.