Artificial Intelligence in Healthcare Market 2019 - Transformative Power of Artificial Intelligence to Revolutionize Healthcare Sector

Traditionally, the entire healthcare system was solely involved in cure of diseases and delivering diagnosis. However, the industry is rapidly moving towards outcome-based care, shifting from its traditional outlook. As the demand for intelligent medical solutions skyrocketed, the healthcare industry witnessed the advent of artificial intelligence (AI), robotics, and other remarkable technological advancements. Integrating AI and robotics in day-to-day operations promises to transform the healthcare sector in the coming years.

Recent Instances of Artificial Intelligence Making Way into Healthcare Sector

AI Used to Design Inexpensive Heart Disease Detector

As per World Health Organization’s (WHO’s) factsheet, nearly 17.9 million people die every year from cardiovascular diseases, which is 31% of overall deaths recorded worldwide. Furthermore, the Centers for Disease Control and Prevention finds that heart failure afflicts nearly 5.7 million people in the US alone. WHO says that 75% of CVD deaths occur in middle and low-income countries. Therefore, access to an inexpensive and ubiquitous method of screening is the need of the hour.

A Mayo Clinic study conducted at the start of 2019 found that incorporating artificial intelligence in electrocardiogram can help in early detection of asymptomatic left ventricular dysfunction, a condition widely accepted as a sign of heart failure. The research team also discovered a high level of test accuracy, which is comparable to common screening technologies such as mammography used in breast cancer diagnosis.

AI-integrated electrocardiogram can extract information on previously hidden heart ailments accurately. Furthermore, it makes the whole process more inexpensive. The technology therefore holds great promise for saving lives in future.

Philips Introduces AI-enabled Oncology Solution

The use of Artificial Intelligence Market in healthcare is not limited to a single product category, rather it can be put to use in a plethora of jobs across the healthcare spectrum. AI also finds use in subspecialties, which were manual processes not a long while ago. For instance, an increasing number of healthcare organizations are leveraging artificial intelligence to facilitate electronic patient record. Market leaders such as Philips and Siemens recently demonstrated the use of AI in exploring patient data, relevant to particular case areas.

Last year Philips showcased its novel Intellispace Oncology software, which offers an overview of a patient suffering from cancer on a single screen.  This integrated oncology solution supports precision medicine programs, helping oncologists reach treatment decisions. The software shows individualized data of a cancer patients, providing information on all patient encounters. These include procedures, imaging exams, labs, pathology, and other related data.

The software is designed to aid complex treatment decisions. In addition to this, Intellispace Oncology software provides insights, which are based on evidence-based decision tools, promoting guidelines adherence. 

AI-pathway Companion by Siemens Promises to Expand Precision Medicine

Similarly, AI-pathway Companion from Siemens aims at expanding precision medicine. It uses AI-based decision support to accelerate decision-taking with regards to diagnosis and treatment. AI-pathway Companion is an AI-based clinical decision support system, designed to support physicians in reaching therapeutic decisions along the clinical pathway. The software optimizes various processes along clinical pathways thus ensuring successful patient management. It offers clinical status of each patient on the basis of artificial intelligence and data integration.

Integration Artificial Intelligence in Healthcare Can Help Better Patient Care

The ever-increasing volume of medical data of a patient can be used for a more personalized and efficient diagnosis and treatment, which also is known as precision medicine. Contrary to this, health data obtained from clinical examinations, genetics, imaging, laboratory results, for example, continues to remain in isolated silos. This is due to the absence of data integration, which may lead to errors in clinical procedures. Incorporating artificial intelligence can fundamentally reshape the healthcare landscape, as it offers an inexpensive medium of accessing the aforementioned data.