Data Science in Healthcare
The Change:
Everything in this world is Data. The average human body generates 2 terabytes of data per day. This mainly includes the functionality of the brain, sugar level, heart rate, Blood pressure, stress level, and many more. To manage such complex data, we have more advanced technologies, one of that is Data Science. It helps in maintaining track of a patient’s health by utilizing recorded data.
Earlier, doctors and hospital administrators couldn’t handle such an accurate track of patients and couldn’t handle large amounts of data at the same time. Larger files of the patients and tracking exclusively different parameters were hard. And because of the lack of proper treatment, the patient’s condition was considerably worried. Now it is quite possible to detect disease symptoms at an early stage. Doctors could also monitor a patient’s condition from remote locations.
Data Science is the Game changer in Industry. Not only in data science but also in other industries it created a great impact. It is an essential component and determines that has changed the medical world. It created a significant impact on treatment and diagnosis.
The strategies to be followed:
Than the traditional approach of data management, hospitals could use advanced technologies. As the amount of data being analyzed increases, the need for more powerful computing resources should also be increased. Another important thing to be noted is, a large amount of data should be handled. Larger datasets mean that hospitals can analyze deep-driven details about each patient’s condition, which allows them to make better diagnoses and provide better treatments.
The key component of determining the best treatment or care plan for patients is using advanced analytics. By combining individual records with historical data of a patient, we could determine better how an individual responds to treatment which improves patient outcomes. Using Machine Learning Algorithms, we could improve the quality of care provided to patients. As ML algorithms are based on certain patterns, it makes the flow easy for medical professionals to develop an accurate diagnosis-based patient’s medical record.
Some Significant Fields:
Cancer has become a quite common word in today’s world. We come across terms like ‘Blood cancer, Testicular cancer’ etc. But ‘Breast Cancer’ is the prone term often heard in recent years. The definition of Cancer given by ‘The National Cancer Institute (NCI)’ is “Cancer is a disease in which some of the body’s cells grow uncontrollably and spread to other parts of the body”.
Finding a cause requires deep research and analysis of vast amounts of data which includes patient records, genetic information, and mainly the cancer tumor samples. As mentioned earlier, approaching ML Algorithms could generate good amounts of positive outcomes. The algorithms could be trained to identify the patterns hidden in large datasets and make predictions.
Another significant disease that is non-excludable in today’s world is ‘Diabetes’. It has a great impact considerably on the youth population. “Indians are known to develop type 2 diabetes at a lower BMI. A trial published in the year 2014 demonstrates that 46% diagnosed under 40 years in India” says TOI.
National Institute of Health says, “India ranks second after China in the global diabetes epidemics with 77 million people with diabetes. Of these, 12.1 million are aged >65 years, which is estimated to increase to 27.5 million in the year 2045.
Data Science could make a remarkable impact on these two diseases efficiently. Not only in maintaining the tracks of patients and predicting the possibility of diseases. We could also make possible predictions based on the medications and diagnoses undergone really crates impact or not.
As we know Data science is a complete package of Mathematics, Statistics, and Probability, and we could also find the correlation based on the data provided. For example, We could see the correlation between the medication and outcome. If there is a positive correlation between them, we could take the inference that the medicine creates a positive outcome, in another case it’s vice versa. If we can’t find any correlation, we could stop the medication and prefer some other drugs or various processes for the development of the patient. This is just a simple example to understand how data science could work at its basic level. We could also create visualization which gives a better understanding of data.
Conclusion:
The Medical world evolves day-to-day. New implementations and the introduction of Data science to this field surely create a massive change that gives positive belief to the commoner that technologies can be used productively to save human lives. There are 2 stages in every problem/ error. 1. Identifying the problem, 2. Solving the problem. We are at stage 1. These measures predict the disease, keep track of the patient’s health and provide the outcome for the patient.
Just think how cool it is?! The prediction that is made by a Machine Learning Algorithm saves the life and extends it, is fair in this unstable world!
- Ranga Bashyam G
(Data Science & Machine Learning Enthusiast)
Dated: 30/05/2023
