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Detecting an abnormality in a patient’s condition and correctly interpreting the result is probably one of the core stakes of medicine with, unfortunately, life-threatening consequences when mistakes are made. Patients’ health greatly depends on the quality of the diagnosis both in terms of speed and analysis standards, which cannot be taken lightly.
Improving the process is a constant imperative for the medical sphere at all levels, from the doctors to the medical industries. This is why advanced diagnostic devices such as IBM Watson for Oncology – an Artificial Intelligence (AI) used by doctors in cancer treatment design – are starting to spread around and even supplanting the traditional procedure.
Machine learning process enables the diagnose machines to analyze and interpret medical cases in a short period of time. For example, melanoma detection devices compare the picture taken of the suspicious mole to a large database like the ISIC Archive. It is composed of more than 13,000 of analyzed skin lesion pictures among which about 1,000 of melanomas. At the end of this process, the machines suggest a diagnosis, more efficiently than an experienced doctor. Once diagnosis delays are reduced, the whole medical process will lead to an increase in time efficiency: shorter analysis means a faster diagnosis rate and shortened waiting-lists. Physicians can then focus on other tasks, where human capabilities cannot be substituted by technology.
An experiment was realized confronting a melanoma detection machine and 58 dermatologists’ analytical capabilities. The result showed that those devices were not only quicker but also committed fewer mistakes. They tend to detect abnormalities at an early stage, leading to earlier patient care, thus increasing chances to recover. In addition to this, the machines are also less prone to raise false alarms. This reliability gain has real positive outcomes resulting in less unnecessary interventions such as biopsy, which can be quite invasive.
Although a certified doctor must be ultimately consulted, those machines could be implemented at GPD’s offices. This measure would expand the access points to diagnose since the expertise being held in the computer does not have to be placed only in specialists’ clinics. Some companies like RetinAI, take it a step further by developing apps that can provide remote diagnosis through the simple use of a smartphone.
Those outcomes will benefit for all and only represent a small portion of all the advantages machine led diagnostics can offer. In the long run, this would also result in an overall diminution of medical costs, advanced technologies making medicine more efficient than ever.
To enable trustworthy medical diagnoses and treatments, it is crucial to choose the right Contract Manufacturer for your medical electronic devices. An ISO 13485 certified EMS partner can effectively support you at each step of your product lifecycle. Our years of experience enable us to master all security, quality and hygienic requirements. Asteelflash is certified ISO 13485 in France, Germany, USA, Mexico, and China and we build Class I and Class II Medical products. We are your reliable Electronic Manufacturing Services partner for your medical project.
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