How is AI Transforming Healthcare Faster?

Healthcare and life sciences sectors are among the leading industries witnessing massive advancement and innovation led by artificial intelligence. AI algorithms can make connections in multiple datasets and interpret the information obtained to boost advancements in drug research and discovery, 

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Nitin Nijhawan, CDOicon

Healthcare and life sciences sectors are among the leading industries witnessing massive advancement and innovation led by artificial intelligence. AI algorithms can make connections in multiple datasets and interpret the information obtained to boost advancements in drug research and discovery, improve the role of robotics in assisting in complicated surgeries, and identify social determinants influencing the government’s health investments and individual care plans.

Technology is becoming instrumental in leading a radical transformation to improve accuracy, efficiency, and enhanced patient outcomes. AI has evident potential to make healthcare more sustainable and scalable. Managed IT services for healthcare can help medical practitioners, doctors, and scientists augment clinical resources through AI and ensure optimal treatment results.


5 Ways How AI Is Leading a Fast-Paced Healthcare Transformation 

1. Facilitating Disease Detection and Diagnosis

Heart disease is responsible for a high number of disabilities and deaths worldwide. This is one prominent area where the healthcare industry is capitalizing on machine learning technology to build algorithms that quickly determine people likely to be at risk. Plus, healthcare software development can help you obtain more accurate results, unlike those of other guiding systems.

Google’s healthcare technology segment, Verily, introduced an algorithm (backed by published research) that can detect early signs of a heart condition that appear in the eyes.

Computer imaging is another AI-based technology that led to the development of advanced algorithms for effective disease detection. This also includes the detection of melanoma, a type of skin cancer. Its survival rate varies between 15% to 65% depending on where the patient is, from early stages to terminal stages. However, some studies show that this technology can improve the survival rate to 98% after 5 years.


2. Crowdsourcing Treatment Options and Monitoring Drug Response

Modern treatment models in the healthcare sector are more data-driven as doctors emphasize early detection and prevention of diseases. And the availability of data in abundance provides a window of opportunity to use and benefit from AI. Healthcare software development services can help integrate machine learning systems to organize and analyze data. As a result, data scientists and clinicians will gain deeper insights into a person’s overall health and can develop customizable treatments to achieve far better results.

Similarly, successful diagnosis and treatment depend on the method of gathering and aggregating insightful clinical information with other datasets. To that end, AI has been integrated into the working of social media platforms that enable individuals to connect and share information about different treatment options. They can also obtain details about various trials of drugs available on the market. This results in data generation in high volumes, allowing the data scientist to continue to track a patient outside of a clinical setting.


3. Tracking and Observing Health Epidemics

AI-powered systems can detect a looming health epidemic and enable authorities to take timely actions to prevent and control health threats. Artificial intelligence systems can quickly sift through and gather a myriad of data from multiple digital platforms and offer insights by analyzing this data with bio-geographical, ecological, and public health information.

The Ebola outbreak in 2014 is an apt example of understanding AI’s influence on our ability to monitor and predict a disease outbreak. Scientists and researchers developed AI-based algorithms that helped detect bat species that are likely to carry and spread the disease. This understanding helped them foresee a potential future outbreak with an accuracy rate of 87%. This incident demonstrated the potential of AI in effectively classifying, predicting, and preparing for possible health epidemics.

The powerful capabilities of AI can be applied globally to develop all-encompassing disease databases where everyone in the healthcare sector will have easy access to all discovered parasites and pathogens existing in humans and animals. Healthcare IT consulting services can help you have such information at your disposal at all times to save more lives.


4. Virtual Assistants Aiding Communication Between Patients and Physicians

Patient engagement in healthcare focuses on medical professionals’ efforts toward establishing trust with their patients. This is crucial for continued care and benefits all the parties involved, including physicians and insurance companies.

AI has introduced a new paradigm into patient-doctor interactions. The growing use of machine learning has resulted in game-changing software development for healthcare. These software programs are designed to learn the best ways to communicate with patients. They can present difficult medical terminology and concepts in easy-to-understand bits of information for patients. This creates a frictionless approach and enables physicians to access information or results needed for the patient quickly. This also enables patients to obtain the information and results that patients need quickly.


5. Improving Clinical Documentation for Patient Care Management

Computers have the processing ability to analyze heavy loads of data in a second to classify different sets of information, outline patterns, and even predict an outcome with a much higher accuracy rate. Advanced AI algorithms streamline healthcare data analytics by allowing easy and quick access to seemingly disconnected data points, like user-written patient notes.

Tools based on machine learning can be applied to detect irregularities, as they can compare a high volume of such notes. Thus, the tools can determine the outcome and obtain insights into positive outcomes. Similarly, doctors are alerted of missing data and if procedures are to be further clarified to create a better analysis for the end user.

Deep Neural Networks (DNN) is a series of algorithms developed to understand complex data patterns across multiple inputs, like the information available in written clinical documentation. Through their numerous nodes, deep nets can clearly define concepts in messy datasets that go undetected in manual analysis. These nodes must be connected to collect and process information that is then classified and leveraged in medical protocols.



AI-powered solutions are gaining momentum in the healthcare industry and are expected to achieve a stronger, more meaningful impact on the global healthcare industry. With AI-based software development in healthcare, clinicians will have advanced technical support in disease detection and diagnosis, treatment planning, and timely identification of risk factors. All these improved healthcare capabilities will ultimately enable the healthcare sector to deliver the most impactful and personalized patient care.

VLink is your best source for hiring managed IT services for healthcare backed by expert technical support and guidance. Our goal is to transform your healthcare practices and administrative tasks with new digital technologies to improve patient care experience as well as medical efficiency and outcomes. Let us help you install comprehensive IT applications support or software that performs tasks you need help with. Contact us to schedule a consultation.

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