Digital Health In Plastic Surgery And Cosmetics

On February 9, 2037 at 6:48 a.m. your smart sleep alarm nudges you to wake up. Picking up your phone and activating the front camera, you take your daily selfie. This one is not for social media but rather it’s to have a smart algorithm analyse the picture. It will subsequently determine whether your personalised ointment is effective against those pesky acnes. 

After getting a report in seconds, you make your way to the bathroom to freshen up before making breakfast. As you sip your coffee, you get a reminder from your telehealth app that your dental surgery is coming up later this week. It also sends a notification that lets you visualise and customise, through augmented reality (AR) technology, how you would like your teeth to look like after the reconstructive procedure.

2037 might seem like it’s in the distant future, but the technologies depicted are already a reality today. Artificial intelligence (A.I.), AR, facial recognition technology and other internet-connected tools will give reconstructive surgery, dentistry and healthcare as a whole an overdue facelift; essentially setting the pace for a so-called cyber-aesthetics era. 

These technologies assist medical professionals in their craft, while also democratising access to care and one’s own data outside the confines of the ivory tower of medicine. Join us as we take a peek into the technologies shaping up the future of aesthetic medicine.

A.I. for prognoses, diagnoses and planning in plastic surgery

By utilising A.I.-based technology, plastic surgeons can advance their surgical practice. This is what a recent systematic literature review concluded. The way A.I. can do so is through predicting prognoses and diagnoses that can aid plastic surgeons in decision-making.

For instance, as far back as the early 2000s, researchers developed a machine learning (ML) model that assesses burn depth and healing time based on data from a portable reflective spectrophotometer with some 86% accuracy. The model could further tell which burns would heal before 14 days with an accuracy of 96% and those healing later with an accuracy of 75%. In practice, such insights could help guide physicians regarding which patients need closer follow-ups; as well as which ones can be discharged earlier.

More recently, in 2019, scientists developed a supervised ML model to successfully diagnose jaw surgery patients from a 3D scan. The algorithm can even simulate surgical outcomes in a 3D model. The authors propose that their method can help surgeons in surgical planning as well as patient education.

Facial recognition to tell the medical tale

Ever tried a face filter on Snapchat? It uses facial recognition technology (FRT), whose use doesn’t end with strapping virtual glasses to your face or making a rainbow emerge out of your mouth. Combining image analysis and deep neural networks, FRT recognises and interprets patterns from facial characteristics which can reveal a range of medical conditions.

Source: https://becominghuman.ai/

For example, the Face2Gene app allows clinicians to detect rare genetic conditions like Cornelia de Lange syndrome. These patients exhibit characteristic facial features, but that can be missed by physicians. This is because they simply might not have come across those during their clinical practice.

Another app developed by Nuralogix uses FRT along with transdermal optical imaging to extract facial blood flow information from the face. This allows the app to estimate stress level, heart rate and a range of cardiovascular parameters from your phone’s camera. However, the company states that their app is “intended to improve your awareness of general wellness” and isn’t meant for medical purposes.

Virtual assistant for surgical FAQs

Surgical patients have a lot of questions buzzing around their heads; but they might not always find the opportunity to ask or get an answer from physicians. A virtual assistant could fill this gap.

Researchers from the Mayo Clinic shared their findings in 2020 after developing an A.I.-based virtual assistant to answer 10 frequently asked questions (FAQs) queried by plastic surgery patients in their institution. After a training period, their smartphone app provided an appropriate answer 92.3% of the time.

The authors already anticipate the integration of such an assistant in the clinical setting. It could serve as a means to improve patient support and free up surgeons’ precious time.

Getting your new smile on with AR

When it comes to reconstructive and aesthetic procedures, it might prove challenging to visualize the end results on the actual patient. However, with AR technology, patients can see how their appearance changes after a procedure, even before entering the OT.

This is already prevalent in dental practice such as with the AR apps developed by SmartTek and Kapanu. These use a phone’s camera to overlay virtual depictions of the improved set of teeth prior to the procedure. This allows patients and dentists to configure features of the dentition such as height and spacing to their liking before they even enter the surgery room.

Similarly, to help potential customers get an idea about how they will look like after straightening their teeth with the company’s aligners, Invisalign developed an online “smile visualisation” tool. By uploading a selfie, they can see a computer-generated simulation of what their smile may look like after the Invisalign treatment. 

Personalised skincare

In the introductory paragraph, our futuristic depiction made mention of personalised ointment. Skincare devices are already available today that enable one to order such products at home. Shiseido’s Optune smart skincare device released in 2019 does this. Its companion A.I.-based app analyses photos of the user, their sleep pattern for any disruptions and location-based environmental data such as temperature and humidity to create a custom moisturiser that is then shipped to the customer. 

Source: https://uk.spotscan.com/

For those suffering from acne, L’Oréal’s La Roche-Posay brand and Chinese tech giant Alibaba Group launched the Effaclar Spotscan. Trained on thousands of images of different skin types and spots, their A. I.-based app analyses selfies to identify the user’s type of acne lesions. Subsequently, it provides personalised skincare tips as well as alerts users if they should consult a medical professional.

An ethical cyber-aesthetic future

Since several of these technologies poised to shape the future of aesthetic medicine involve A. I. and virtually all deal with sensitive personal data, ethical use and development of these tools becomes a must.

In a previous article, we highlighted the inherent bias in the health data fed to algorithms. Authors of the aforementioned systematic review also note the importance of quality assurance of data used in A. I. algorithms; especially when it comes to augmenting patient treatment decisions. “The data sets used to train the ML systems must be representative of the population for which it is intended,” they propose. “Providers must make efforts to optimise the data and algorithms to best benefit their patients.”

Source: www.geneticliteracyproject.org

Of course, now that data is the new oil, privacy concerns are heightened when these tools are employed by patients. When such apps and devices are rolled out, the privacy and security of users’ data must be guaranteed. Otherwise, adoption and general trust towards such options will plummet. 

Only when an ethical development of the underlying algorithms and secured handling of user data is assured will each and everyone of us make the most out of the convenience of our cyber-aesthetic tools. Hopefully, it will happen before 2037.

Dr. Bertalan Mesko, PhD is The Medical Futurist and Director of The Medical Futurist Institute analyzing how science fiction technologies can become reality in medicine and healthcare. As a geek physician with a PhD in genomics, he is a keynote speaker and an Amazon Top 100 author.

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