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Industry 4.0- AI Technology for Medical Uses

Introduction

Google AI can predict cardiovascular problems: Google CEO Sundar Pichai-YouTube. This video shows the amazing revolution in AI technologies ~ Google is developing IT technologies that can use the smartphone camera to scan the retina of the eye and predict if the person has eye & vision issues if the person has heart & cardiac issues. This is possible due to the advanced data centers built by Google where massive volumes of data are analyzed in seconds to diagnose and feedback to the smartphone use about his health status.

AI Application in Healthcare

AI technology is breaking new ground, as it has implications in more psychological realms such as experience, intelligence, and judgment of the experts. Google AI Healthcare, also in the fall of 2018, created a learning algorithm, LYNA(Lymph Node Assistant), that analyzed histology slides stained tissue sample) to identify metastatic breast cancer tumors from lymph node biopsies. This isn’t the first application of AI to attempt histology analysis, but interestingly this algorithm could identify suspicious regions undistinguishable to the human eye in the biopsy samples given. LYNA was tested on two datasets and was shown to accurately classify a sample as cancerous or noncancerous correctly 99% of the time. Furthermore, when given to doctors to use in conjunction with their typical analysis of stained tissue samples, LYNA halved the average slide review time.

Recently, other imaging-based algorithms showed a similar ability to increase physician accuracy. In the short term, these algorithms can be used by doctors to assist with double-checking their diagnoses and interpreting patient data faster without sacrificing accuracy. In the long term, however, government-approved algorithms could function independently in the clinic, allowing doctors to focus on cases that computers cannot solve. Both LYNA and DLAD serve as prime examples of algorithms that complement physicians’ classifications of healthy and diseased samples by showing doctors salient features of images that should be studied more closely. These works exemplify the potential strengths of algorithms in medicine, so what is holding them back from clinical use?

Conclusion

AI technologies are expected to bring innovations to the existing medical technologies and future health care. The currently available AI-based health care technologies have shown outstanding results in accurately diagnosing and classifying patient conditions and predicting the course of diseases by using the accumulated medical data. Accordingly, these technologies are expected to bring contributions in assisting the medical staff in the treatment decision-making and in the process improving the treatment results. However, AI-based health care technologies currently have various issues regarding privacy, reliability, safety, and lability. For the AI technologies to be more actively applied in health care, general public awareness of AI, the establishment of standardized guidelines, and systematic improvements will be required in the future in addition to the technological advancements.

 

Mansoor Ahmed is Chemical Engineer, web developer, a writer currently living in Pakistan. My interests range from technology to web development. I am also interested in programming, writing, and reading.
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