A 2015 Cancer Research UK study found that many people suffering the ‘10 red flag signs’ of cancer –such as a persistent cough, a mole changing size or color, or unexplained weight loss– didn’t visit a medical professional because they thought it was ‘trivial’.
Whether it be due to long wait times, expensive private health-care costs, or just a fear of bad news, Millennials are notoriously bad for seeking medical advice at an early stage, instead choosing to ignore the issue until it gets worse, or leaning on online diagnosis platforms like WebMD.
The problem is made worse by a lack of quick and easy access to medical professionals. In the UK, wait times have been branded ‘a national disgrace’ and a NHS representative described hospitals as being so overwhelmed patients could die. In the U.S. the Affordable Care Act has left doctors struggling to manage their workflow, and patients waiting long periods for essential appointments.
And even when you do manage to see a doctor, a first study suggests that medical professionals might be increasingly missing signs for life threatening conditions like bowel, ovarian and skin cancers due to work pressure. Early detection can dramatically improve the chances of recovery, and the rise of a new generation of digital diagnostic tools will be supportive to both efficiency and accuracy for doctors. Enabling them to handle more patients, and treat them even better. So what are these new tools entering the market?
Across the world health services have rolled out triage systems to determine whether patients need urgent attention, after conducting a consultation via phone or internet. However a British study which included 42 practices, found that instead of saving time and money, phone based triage actually increased the workload for medical staff.
UK based Babylon thinks it has the answer. The health-tech startup has created an A.I powered app which according to early testing can undertake triage assessment to the same level or better than that of human doctors and nurses.
Babylon’s “Check a Symptom” feature, which uses a set of in-app questions can accurately highlight billions of variations of symptoms and the startup claims its A.I program outperformed both doctors and nurses across 102 mock patient consultations, producing a clinically safe outcome in 100 percent of cases, and an “accurate” triage in 90.2 percent.
Rolling out these apps as part of a national or private healthcare system would allow users to assess themselves from the comfort of their own homes, and massively reduce the strain on healthcare professionals, freeing up time for treatment of real illnesses and injuries.
Every year, approximately 70 thousand men and women age 15 to 39 are diagnosed with cancer in the US. Breast cancer is the most common cancer for women in this age bracket, but according to the Young Survival Coalition to date no widely available breast-cancer screening tool has been released.
3D imaging startup Vayyar has created a tool which could revolutionize early-stage breast cancer screening, using a small handheld device which allows users to self-test by placing the sensor against their own breasts. The tool allows users to scan themselves using radio frequency technology, and in less than five seconds, it produces a 3D image of their breast tissue which can identify early-stage malignant growths.
The tool has not been released on the general market yet, but the co-founder Raviv Melamed stated “The goal was to have a low-cost imaging device that every person can use, instead of just experts and people who understand complex technology.”
Even when women go for a check up, there is a reasonable risk that a growth will not be picked up on a scan. According to UK newspaper The Telegraph, radiologists working in overworked and underfunded NHS hospitals fail to identify breast cancer in thousands of mammograms every year. To combat the element of human error, Zebra Medical Vision has created an algorithm which uses machine learning to identify early signs of breast cancer after digesting thousands of previous mammograms. According to Eldad Elnekave, Zebra’s chief medical officer, the self-teaching A.I program can identify up 50% more cases of breast cancer than human radiologists due to it’s extensive databases.
Previously detecting lung cancer required CT scans, which are expensive for hospitals, and normally require long waiting times due to the limited amount of machines available. Lung cancer is not normally detectable until it has progressed to a later stage, by which point it will require serious surgery and treatment, and poses a much higher risk to the patient.
At the Accelerate pitch competition at the prestigious MIT university this May, Astraeus Technologies wowed judges with an amazing creation that can detect lung cancer with just one single breath.
Rather than using expensive CT scans, the startup has created inexpensive ‘L-cards’ and a connected app, which detect the presence of a gas omitted by people with lung cancer. The company is in the process of getting FDA approval for the ‘L-cards’ and the team claim that it will be possible to modify the technology to detect other types of cancer, as these illnesses also lead to the creation of different, detectable gases too.
This new technology is much more affordable and quicker than traditional treatments and could potentially save millions of lives by allowing people to seek treatment at an earlier stage of their illness. Making positive change requires a shift in mentality amongst young people, whereby they become more careful about and active in their own healthcare.
Even though the survival rate for cervical cancer has increased by more than 50% over the last 40 years since health services introduced the Pap test, it still poses a big risk for women in their middle ages. While the survival rate is high compared to other cancers, treatment for cervical cancer can often leave women unable to conceive if the illness is detected at a later stage.
Experts state than many young women avoid getting check ups, due to the evasive nature of the screening process, especially in countries with conservative cultures in Africa, Asia and the Middle East. Dr Alphonse Butoyi, a gynaecologist at Kanombe Military Hospital in Rwanda states that as many as three quarters of women who attend his clinic refuse to take a Pap test.
To make the screening process more comfortable, and also to dramatically improve the discovery rate, Biop has created an optical probe which can accurately identify and classify precancerous and cancerous lesions in just 90 seconds. According to Biop, more than 30% of invasive cervical cancers are missed when doctors use traditional screening methods.
Biop’s probe uses both imaging and non-imaging optics to accurately map out the cervix to its deepest layer and locate and highlight any diseased lesions. Biop’s technology allows gynecologists to identify cancerous and even pre-cancerous tissues in the cervix, at an early stage of malignant transformation, allowing them to take action before the condition develops, and requires more serious treatment.
Big data, machine learning and what’s next for Millennials
Startups like Biop are also harnessing the power of big data, by compiling a database of images from millions of patients around the world, allowing the system to learn and improve over time. Big data and machine learning A.I is playing a big role in the field of diagnostic medicine, and algorithms are being developed which allow analysts to identify cells which are at risk of becoming cancerous, before the transformation takes place.
Researchers at Brown University, have developed a new machine learning image analysis technique to distinguish two key cancer cell types associated with tumor progression. The researchers have created an algorithm which is able to categorize individual cells as either epithelial or mesenchymal with more than 92 percent accuracy.
The ability to remotely assess whether it is necessary to make an appointment with a doctor will hopefully appeal to Millennials, and motivate young people to get checked officially, and start treatment before it is too late. This new technology will also take the strain off medical professionals themselves, by removing the chance of human error, and ensuring that patients who pass through their doors really need to be there. However, until the technology matures, and is approved by governing bodies, it is always best to play it safe and make an appointment with a real human doctor as early as possible.