How Digital Health Helps Oncology

How Digital Health Helps Oncology

Alex D'Souza, Healthcare Tech Outlook | Monday, May 31, 2021

Early diagnosis and personalization of treatment is essential in cancer treatment and cure.

FREMONT, CA: In an increasingly digital business world, people have come to accept that computational approaches have not only improved the understanding of health issues but contributed to the diagnoses of diseases, their prevention, and cures. The treatment of cancer is notorious for being unique to every patient. Even if all factors of the condition are identical, the personalization of medical treatment is vital. Therefore, it comes as no surprise that in the oncological landscape, digital health is playing a pivotal role in tailoring prescriptions to specific needs, enhancing cancer diagnostics and treatment, and facilitating patient care. 

Commercially-available technologies like wearables have started to play a vital role in assisting patients in handling their cancer. Recent research in several US cancer centers concluded that integrating general fitness data using a smart band is a realistic method to reduce unplanned hospitalizations. Often, chemotherapy treatments, coupled with the disease itself, causes nausea in patients. This challenge can be managed with a simple fitness regime, seamlessly monitored by wearables connected to smartphone apps for data logging. 

Even though the technologies for cancer prevention, identification, diagnosis, and prognosis are still far from being available to the general public and far from acting as standalone treatment technologies, the oncological innovations in digital health have progressed since the inception of oncology as a science. With digital health technology offering more affordable and less invasive cancer management solutions, the ability to create a holistic and effective model of managing cancer seems progressively more likely every day in the digital age.

Methods with machine-learning to predict patients' outcomes were launched with modeling for the prognosis of patients with renal cell carcinoma, using collected statistics in sources. With the integration of these additional variables, the accuracy of diagnoses has comparatively skyrocketed. Simply by sharing symptoms in a timely way as they occur, assisting clinicians to better personalize treatment, digital tools like these have been able to extend patients' lives by up to five months.

Check out: Top Oncology MedTech Solution Companies

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