The proliferation of next-generation technologies, advances in computing power and an infinite wealth of data, computers are now taking the front stage to handle varied and complex learning tasks. To our surprise, the success rate is increasing exponentially. In parallel, every sector of an economy is applying complex data analysis, and the adoption rate is going through the roof. The healthcare sector is not far behind where applications of next-gen technologies like artificial intelligence and machine learning- are being used for medical solutions.
A spur of machine learning applications in medical solution is a new dawn in the sector. It is giving new hopes to civilization for effective and all-in-one healthcare solution. Applying machine learning applications for enhanced medical solutions will provide a window to the future where data, analysis, and innovation will cater to the masses. The accelerating power of machine learning will aid in diagnosing diseases and insights generated from an abundance of data will empower physicians and increase the decision-making process. Below are some ways which show how machine learning applications can be implemented for medical solutions and uplift the healthcare sector as a whole.
Enhanced Diagnostics And Identification Of Diseases
One of the ways where machine learning applications are useful to provide a solution in the medical sphere is its ability to identify and diagnose diseases which otherwise are hard to diagnose. Diseases can include fatal ones like cancer which are difficult to ascertain in the initial stage, to many other rare and genetic diseases. One such example is IBM Watson Genomics where cognitive computing is integrated with genome-based tumor sequencing which helps in faster diagnosis. In some places, applications of artificial intelligence are leveraged to develop therapeutic treatments in areas like oncology.
Facilitating Drug Discovery And Manufacturing
Although in its very nascent stage, machine learning applications are aiding in drug discovery and manufacturing process. It encompasses research and development technologies like sequencing and precision medicine which assists in finding alternative paths for therapy of multifactorial diseases. In a recent development, a computer science and engineering student is working on a project where the computer is fed with information about chemical compounds that have or have not worked as drugs in the past. From this input, the machine “learns” to predict which kinds of new compounds have the most promise as drug candidates, potentially saving money and time otherwise spent on testing. Another notable development includes an AI-based technology for cancer treatment and a personalized drug combination for Acute Myeloid Leukaemia (AML).
Medical Imaging Diagnosis
The ability to see through things, machine learning and deep learning have assisted in a technology breakthrough called computer vision. In time to come, advancements in machine learning technology will grow in their explanatory capacity and will be able to see through a wealth of data sources and analyze diseases and tumors with precision.
Personalized treatments are not only effective in pairing individual health with predictive analytics but it also furthers research and accounts for enhanced disease assessment. At present, physicians are limited in terms of choosing a specific set of diagnoses to estimate or predict the risk to a patient based on his past history. Machine learning, in this particular sphere, is moving by leaps and bounds with IBM’s Watson oncology taking the forefront. It leverages a patient’s medical history and generates a plethora of suggested treatment options.
Smart Health Records
A manual collection and entry of medical records is a long haul process. Even though technology has helped to ease the process of data entry, a majority of the processes still takes time to complete. Machine learning has provided a lot of help in this aspect where machine learning based smart health records are the new trend, which will help in clinical treatments, suggestions, diagnosis, etc. Vector machines are aiding in document classification and machine learning OCR (Optical character recognition) recognition techniques are slowly gathering steam.
Machine learning and artificial intelligence based technologies have provided much-needed advancement in predicting epidemics in and around the world. Scientists now have a huge pool of data collected from real-time social media updates, satellites, etc. Machine learning algorithms churn out data to predict everything from malaria outbreaks to infectious diseases. This prediction mechanism has especially helped the third world country to put up adequate medical infrastructures.
Indeed, machine learning is taking healthcare to a whole new level by leveraging technology and making the world a better place to live.