As part of Google’s ongoing initiative to apply machine learning to as many fields as possible, Google has partnered with healthcare institutions to develop new medical tools and techniques using machine learning. These partnerships have proved to be successful over the past year, with machine learning already showing promise in diagnosing diseases and tracing complications. In its blog post, Google announced its success in using machine learning to trace the spread of cancer cells from the breast to the lymph nodes in the advanced stages of cancer. Machine learning has also proved useful in screening diabetic retinopathy, which is the loss of eyesight as a complication of diabetes. Google’s efforts did not stop in diagnosing medical conditions but rather has extended to developing medical equipment and holistic care management with another Alphabet subsidiary, Verily, and other healthcare partners.
At this point, Google feels that machine learning is mature enough to be more involved in the medical field. To better observe what machine learning can do to improve healthcare, the search giant has partnered with medical institutions like UC San Francisco, University of Chicago Medicine, and Stanford Medicine to test how the combination machine learning and clinical expertise could improve the health of a patient. By using de-identified medical information from the hospitals, Google will use machine learning to identify patterns in the patients’ data. The patterns found in the data could help clinicians to assess what the patient may need next. Through providing important data and analysis to clinicians, it could result in smaller costs and increased survival rate of patients.
However, there are numerous obstacles that Google needs to face as it develops machine learning tools for medical practitioners. Among them is the complexity of healthcare data, especially compounded by the lack of standards in organizing patient information. Another concern on the part of physicians is ensuring the privacy of the patients. Despite Google’s efforts to ensure that the medical data is not identifiable and is not mixed with consumer data, as it is still facing intense scrutiny from healthcare regulators and academics. Nonetheless, it is clear that despite these obstacles, Google will continue with its efforts to make the use of machine learning in the medical field more widespread.