Deployment Model (Cloud-based, On-premise)
The global healthcare cognitive computing market is segmented and analyzed for demand and supply by deployment model into cloud-based and on-premise. Out of the two types of deployment models, the cloud-based segment is estimated to gain the largest market share of about 61% in the year 2036. The growth of the segment is primarily attributed to the rising adoption of cloud services in the global healthcare sector. Cloud solutions in healthcare automate backend tasks, streamline telehealth app development, and even make it simpler and safer to share medical records. In addition, owing to the cloud-based options, the efficiency of the healthcare sector has increased and expenditures are reduced as it facilitates using machine learning's natural language processing skills. Moreover, it is also utilized to run crucial applications, collect, and monitor crucial information from large amounts of unstructured data.
End-user (Hospitals, Pharmaceuticals, Medical Devices, Insurance)
The global market is also segmented and analyzed for demand and supply by end-user into hospitals, pharmaceuticals, medical devices, insurance, and others. Amongst these segments, the hospital segment is expected to garner a significant share of around 38% in the year 2036. The major factor for the expansion of the segment size is the increased revenue generated by the hospitals along with the rising patient pool which aids in generating a huge amount of data that needs to be segregated on a daily basis. Hospitals provide patient satisfaction since, all sorts of trained medical professionals, laboratories, and medical equipment are available in a single place. It was noticed that globally, around 65% of people desired to pay more for quality physician consultations. Additionally, the number of hospitals over the world is increasing along with the high investments in enhancing the hospital infrastructure. For instance, the number of hospitals in the U.S. grew from 6900 in 2019 to over 7300 in 2022.
Our in-depth analysis of the global market includes the following segments:
By Technology |
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By Deployment Model |
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By End User |
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Author Credits: Radhika Pawar
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