After data science has come into existence, the way we see the things and interpret have changed drastically. Not only has it helped in the advancement in the field of technology, but also has contributed in many other areas, one of which is the Health sector.
The students out there should take inspirations from different study cases in these fields and try to make there own models and analysis charts for the real world out there, and who knows it can be the next breakthrough in this always advancing field of technology.
From hospitality to manufacturing to oilfields, industries have started adopting sensor-enabled assets for a few years now. Companies have started utilizing sensor data for predictive maintenance and other relevant uses. Electrical devices are being designed with energy efficiency in mind to reduce power requirements. Energy efficiency will be a major focus to reduce global greenhouse emissions. Companies are looking for solutions to reduce energy costs and consumption.
Energy data analytics opens new doors to identify areas of inefficiency and implement targeted energy-saving initiatives. Using machine learning and big data analytics for energy efficiency can help address critical challenges in quality, productivity, and efficiency
2. DATA-DRIVEN FARMING
Momentum around data-driven farming is gathering thanks to the use of technology like soil sensors, drones, and livestock monitoring gadgets to produce reams of priceless information. The end goal is to help agricultural businesses make better, more informed decisions, allowing them to tap into a range of advantages. Key to realizing its potential lies within the part in the middle; the applications and practices which make sense and use of all this information, creating a new era of ‘smart farming’ for the world to behold.
The place where data science has been of most use is that of Healthcare. Many sorts of things have already been done in the field of healthcare. Some of the prominent points have been mentioned as follows:
These are wearable devices which can be worn to monitor health and have regular checks on someone’s health. The amount of data that gets generated daily regarding health is around 2 terabytes. Thanks to advances in technology, we will currently collect most of it, together with information concerning rate, sleep patterns, blood sugar, stress levels, and even brain activity. Equipped with such a quantity of health information, scientists are pushing the boundaries in health watch.
World’s leading technology corporations, like IBM and Qualcomm, are leading the approach in health innovations. In 2015, Apple has joined the race for higher tending with its Research Kit. Yet, there stay many opportunities in the market.
Machine learning algorithms can track a lot of common conditions, like heart or metabolism diseases. Collection and analyzing rate and respiration patterns, the technology will notice the slightest changes within the patient’s health indicators and predict potential disorders. While 600,000 individuals suffer explosive heart stoppages within the US each year, having a chance to anticipate the matter and channelize timely alerts might save thousands of lives.
Another tending issue that involves special attention and routine observation is chronic illness management. With an especially high-fat rate (30 p.c and better in twenty-five states), the variety of probably dangerous chronic conditions, like polygenic disease and high blood pressure, have emerged because of the major risk factors for the US population.
Targeting this specific market chance, Omada Health positions its flagship product as a “first digital therapeutic.” It’s a knowledge science-aided practice of medicine program, aimed toward dynamic patients’ fashion and serving to them keep their weight in restraint and avoid dangerous impacts of the fat on their health. Adopted by people likewise as businesses, the merchandise represents a whole toolset aimed toward reducing the chance of preventable health problems.
Using sensible devices, like scales and measuring device, processing of patient’s activity information to form extremely customized programs for each patient and supply the private health coaches with a chance to achieve deeper insights into the patient’s health and alter the programs on the approach. Moreover, the self-learning rule is continually improved because it sources a lot of patient information from the system.
Increased efficiency and prediction values
The machine learning algorithms have been doing a fine job in predicting the plausible outcomes and are also being used to create algorithms which help in healthcare services very much.
Despite such immense amounts of health knowledge at hand, the diagnostic failure rates are still comparatively high. consistent with the recent analysis by the National Academies of Sciences, Engineering, and drugs, regarding five % of adult patients are misdiagnosed annually within America. This totals over twelve million individuals. Moreover, the PM results analysis shows that diagnostic errors cause roughly ten % of patient deaths.
Targeting this downside, a deep learning startup, Enlitic, employs knowledge science to extend the accuracy and potency of nosology. With $15 million funding, the startup has designed a deep learning algorithmic rule which will scan imaging knowledge (such as x-rays, CT scans, etc.), and analyze it, checking the given results against in-depth information of clinical reports and laboratory studies. Therefore, the corporate claims to deliver up to seventy % a lot of correct results, 50,000 times quicker.
Take for example the Dutch startup, referred to as Bruxlab, that applies similar knowledge science and machine learning algorithms for diagnostic functions. in addition to sound recognition technologies, they assist diagnose and live action symptoms. employing a Brobdingnagian range of audio samples, each true and false, the info scientists instructed a neural network to acknowledge and live teeth grinding symptoms.
With a prevalence rate of up to thirty-one %, an action is kind of a widespread sickness, nevertheless, it’s principally unnoticed because of its symptoms’ hid nature. Thus, a mobile app, powered by knowledge science technologies, presents a big chance for higher designation and a lot of economical sickness watching.
Many other applications like Drones for emergency health services, healthcare chatbots, phone doctors are being used and continuously improved to make this world a better place.