The Technological Revolution in the Health World: The Challenge for Engineers
A study conducted at Stanford University illustrates how technologies from the high-tech field will change the world of health and medicine, while at the same time posing a question mark regarding the feasibility of the practical application of similar technologies for the benefit of the general population.
The Stanford researchers trained an algorithm to diagnose skin cancer through deep learning. The algorithm was trained to detect skin cancer or melanoma by identifying 130,000 images of skin lesions, similar to the preliminary visual diagnosis performed by dermatologists. Stanford’s deep learning algorithm was tested against 21 dermatologists who examined the images of the lesions and were asked whether, based on each image “they would proceed with biopsy or treatment, or reassure the patient”. The study findings showed that the algorithm matched the performance of the 21 dermatologists in deciding on the best course of action with regard to all the images.
In the U.S. alone more than 5 million individuals a year are diagnosed with skin cancer. The most fatal form of this cancer, melanoma, can be cured if it is detected in its earliest stage and treated properly. Survival rates vary significantly depending on the stage at which the patient was diagnosed, between 15% if detected in its latest stages compared to 65% with early detection[WU1] . The cost of treating skin cancer to the U.S. healthcare system amounts to USD 8 billion annually. Thus, the significance of early detection of skin cancer is critical for the patient as well as for the healthcare system: treatment of a patient whose complaint is diagnosed by a physician in the early stages is 20 times less expensive than a complaint treated at a late stage.
Suitable training is necessary
The annual Precision Medicine World Conference (PMWC) focused on the question: “How can AI technologies and database analysis technologies be utilized to foster smart, precise and personalized medicine”.
There has been significant progress in the use of information technologies from the high-tech field in recent years - to collect and analyze information and for artificial intelligence, alongside pronounced progress in technologies from the biotech world – genetic information sequencing, diagnostic tests and clinical data monitoring. In the near future these developments will enable us to apply tools from the high-tech world, particularly AI, to the health care world – allowing for the development of smarter medicine at the drug development and patient diagnosis stages and in providing personalized treatment.
A significant challenge that may tip the scales in the application of technologies in the health care world has to do with the engineers who will carry this out. At present engineers do not have the necessary knowledge about health care and they lack understanding of the range of needs and considerations. The significance is far-reaching in terms of the market success of a product that is developed, in applying the technology, and above all – in the actual contribution of the product to health care in general and to the patient in particular.
Suitable training of engineers who will have knowledge in the health world will dictate the diffusion rate of technological innovation into this area – in other words when will most of the population be exposed to and enjoy innovative technologies in the health world?
