AI in Healthcare

We have seen magical machines/robots in movies with the capability to scan for any illnesses or injuries and can give suggestions for treatment. We have not wondered then, but that is Artificial Intelligence.

Yes! That is fantasy, but with Artificial Intelligence/Machine Learning, the technology has evolved, and now this is reality, at least some part of it. Engineers/R&D teams are working to make healthcare AI become a practicality and reality from fantasy. 

Here, I take a look at the positive impact of artificial intelligence (AI) and edge computing technologies in developing devices to improve healthcare. 

Why Artificial Intelligence is needed in Healthcare

The pandemic and post-recovery illnesses have clearly shown the surging need for an improved healthcare system due to the imbalance between the healthcare workforce and patients.

Although, over the decade, there has been an incredible improvement in healthcare systems, still, with the current situation and the pandemic, healthcare systems face growing demand, rising costs, and a workforce struggling to meet its patients' needs.

 To deal with such future situations, we need to scale the healthcare system, maybe something virtual or a combination of virtual and physical!

AI/ML tools can automate simple tasks at scale and fraction of the time. The usage of machine learning (ML) and other cognitive technologies can help machines mimic human behavior/ patterns to analyze and respond. Artificial Intelligence is already helping the medical industry generate valuable insights and better care. AI has proven to be a boon for the healthcare industry by detecting links between genetic codes, using surgical robots, or even maximizing hospital efficiency.

Artificial Intelligence (AI) helps deliver faster results by diagnosing accurately and reducing errors.

AI and Healthcare

The Healthcare system is going through a change driven by technologies like artificial intelligence (AI).

Artificial intelligence (AI) is poised to reshape the healthcare system and potentially improve doctors' and patients' experiences.

AI-powered instruments, medical devices, and technologies transform the healthcare system by bringing data processing and storage closer to the source. It helps to reduce latency and helps in making real-time decisions. AI on edge offers many advantages to Healthcare

Robust infrastructure
Ultra-low latency processing
Enhanced security
Bandwidth savings
The harnessing of operational technology domain knowledge

The automation in healthcare systems is helping the workforce in the medical profession with improved decision-making and diagnosis.

Edge Computing and Healthcare

AI on the cloud suffers from bandwidth congestion, network reliability, and latency issues. These may result in delayed responses that may result in an unfortunate event. Healthcare organizations are adopting edge computing for scalability, reliability, security, performance, and real-time insights to address these concerns. 

Modern medical instruments at the edge have accelerated computing built into regulatory-approved devices. These features include improved medical image acquisition and reconstruction, workflow optimizations for diagnosis and therapy planning, measurements of organs and tumors, surgical therapy guidance, and real-time visualizations and monitoring.

Smart hospitals are also integrating edge computing and AI workflows into technologies such as patient monitoring, patient screening, conversational AI, heart rate estimation, CT scanners, and much more. These technologies can help identify a patient at risk of falling out of a hospital bed and notify the nursing staff.

Challenges of adopting AI in Healthcare

These intelligent virtual systems are dependent on rapid communication, least redundancy, and involve high-performance computation (HPC). AI is transforming the healthcare system by modernizing the conventional diagnosis, treatment, and drug development approach. However, limited resources to motivate the large-scale public is impacting these health programs. Apart from these other challenges while scaling healthcare systems using AI are:

• Data privacy: legislation limiting data rights and access,
• Technology improper expectations surrounding the technology,
• Skilled labor shortage of data scientists
• Increased cost, demand, and required workforce

Healthcare with AI and Semiconductors

Many AI applications, including virtual assistants like Siri, Alexa, and google assistant, are excellent examples of conversational AI and are more advanced than regular chatbots with answers.

These diverse solutions and emerging AI applications use hardware as a core enabler of innovation, especially for logic and memory functions.

The ability of AI to drive performance in Healthcare is tied to semiconductor innovations. For developing intelligent virtual systems, we need purpose-built silicon. Semiconductors play a crucial role here, as it helps provide user input, display, wireless connectivity, processing, storage, power management, life-saving equipment, and NLP infrastructure. AI offers enormous opportunities to Semiconductor companies, especially in compute, memory, and networking segments.

Semiconductor-rich devices have become increasingly ubiquitous in developing solutions for numerous problems throughout this global pandemic. Semiconductors, the chip's brain, are crucial for analyzing and responding in AI-based healthcare systems.

Benefits of AI in Healthcare

Health organizations have accumulated substantial data sets in the form of health records and images, population data, and clinical trial data. Artificial intelligence in Healthcare uses machine learning models to search medical data and uncover insights to help improve health outcomes and patient experiences. AI tools help analyze CT scans, x-rays, MRIs, and other images for lesions or other findings that a human radiologist might miss in medical imaging. During the Covid-19 pandemic, many healthcare organizations tested new AI-supported technologies, such as algorithms designed to help monitor patients and AI-powered tools to screen COVID-19 patients. AI can positively impact the healthcare system in many ways, some examples showcasing the usage of AI for bettering the Healthcare are 

• Improved accuracy and efficiency in the operations
• Providing user-centric experiences
• Accelerates clinical decisions
• Early detection of disease
• Accurate diagnosis and treatment
• It prevents high-risk situations and reduces hospital re-admissions
• Increases medical workforce efficiency
• Accelerated drug development

Summary

A faster and more efficient diagnosis may help the patient soon on the road to recovery. AI helps to predict early and allows for practitioners to make more efficient and logical decisions, advancing the care for patients, which in the end, is the goal. Further, the potential of AI-based tools for elderly care and the rising potential of AI technology in drug discovery, imaging, and diagnostics to fight COVID-19 are expected to create a growth opportunity for artificial intelligence in the healthcare market.