What is data science?
Data science is the process of applying algorithms, methods, and systems to extract knowledge and insights from structured and unstructured data. Data Science includes all the tools, techniques, and technologies that help us process data and use it for our benefit. It is an interdisciplinary mixture of statistical inference, data analysis, algorithm development, and technology to solve analytically complex problems.
There are three main components of Data Science
- Data organization
- Data aggregation
- Data delivery
How data Science and Big Data helping humans?
Big Data is a variety of tools, approaches, and methods for processing structured and unstructured data, making it possible to use this data to solve specific problems and achieve goals. Using Big Data analysis, retailers can know ahead of time what products will sell well, telecoms can predict when and when a customer wants to switch carriers, and insurance companies can assess how safe their customers are driving.
Among other things, Big Data analysis allows us to better understand and predict disease epidemics and find the most effective treatments.
Data science helping humans
Let’s look at how data science is transforming human life in the healthcare sectors helping in medicine and biotechnology. Traditionally, medication has relied solely on the expertise of doctors. Therefore, the doctor should offer the patient an appropriate treatment based on the symptoms and findings. Now physicians are actively using data science to improve patients’ lives and predict diseases at an early stage. Advances in image analysis have revolutionized the diagnosis of microscopic tumors and have saved thousands of lives.
However, considering various circumstances, the decisions and opinions of professionals do not exclude the possibility of error and misdiagnosis. The power of data science comes to the aid of doctors and patients by providing more accurate diagnostic indicators.
Here are some examples of the application of new technologies in medicine for you.
Medical imaging and image analysis
These techniques for the non-invasive examination of human internal organs allow us to identify abnormalities and diagnose diseases.
In the past, doctors manually checked images obtained during examinations and found irregularities in them. In the case of microscopic deviations with this approach, there is a high probability of error and misdiagnosis. With the advent of deep learning technologies, it has become possible to find such anomalies with high accuracy. They are now searched to use image segmentation and processing techniques such as support vector machine (SVM) violation detection.
Several other techniques are used to improve images and improve the accuracy of the result. For example, the big data platform Hadoop uses MapReduce to find parameters used in various tasks.
Data science also plays an essential role in patient health monitoring. For example, IoT (Internet of Things) devices made in portable medical gadgets monitor the heartbeat, temperature, and other medical parameters of users. These can be blood glucose meters, smartwatches, gadgets for blood analysis, temperature monitoring, pressure, pulse, etc.
Using predictive disease modelling, data scientists have developed comprehensive virtual patient care platforms. Based on the entered symptoms, it is possible to get an idea of diseases in the patient based on the confidence factor.
There are also virtual assistants in everyday tasks for patients with psychological problems such as depression, anxiety, or neurodegenerative diseases.