Artificial intelligence is playing a crucial role nowadays in healthcare industries. The innovations have become easy and are promising better outcomes in terms of patients’ health. Additionally, the efficiency of workflow in hospitals is also improving with artificial intelligence integration. Considering this, the revolution has now reached the AI in healthcare applications. From diagnosis to offering home-based care and monitoring patients at every stage after treatment, everything can be done efficiently. To shed more light on How Artificial Intelligence is Revolutionizing Healthcare Apps, this article will briefly discuss 5 real-world examples of AI in Healthcare Applications.
Enhancing precision in patient positioning and CT imaging
For a radiology department, the increasing number of patients is a challenging situation. The reason is that the department has to keep the consistency and ensure image quality. As computed tomography is majorly utilized in healthcare, they can leverage AI to streamline the workflow to keep up with efficiency.
In CT, mispositioning is a common challenge; thus, using AI can help in guiding with the right position for the medical exam to begin. Furthermore, it will also assist beforehand to provide information related to the radiation dose (high/low).
Accelerate Image Acquisition in MR
MR department has to scan a large number of patients. Therefore, they are mostly burdened with work and also face workforce shortages. The AI integration helps in accelerating the process which will improve the productivity and also help in cost reduction. It will also lessen the burden of the workforce. Artificial integration lessens the examination period and also increase the first time right scan that keeps patients at ease.
Ease the Ultrasound Measurements
The artificial intelligence integration in the ultrasound helps in keeping manual and repetitive process at bay. To visualize and evaluate patients’ heart function is an indispensable part in cardiac care. There are some measurements that need to be taken care of, and they are time-consuming. Henceforth, AI implementation becomes important, which benefits professionals by allowing them to accept and do modification.
Image reading in radiology
In radiology, image segmentation and quantification are required. AI can help focus on the high-level interpretation of images and assist in making the right decision.
For example, AI can detect small changes in brain scans, improving multiple sclerosis diagnosis by 44% while saving time. In lung scans, AI finds nodules 26% faster and catches 29% of those that doctors might miss. This support is especially useful for busy radiologists, leading to better and quicker care for patients.
Enhancing teamwork in cancer care
Cancer care involves managing multiple medical aspects and gathering the right information for treatment decisions. AI in Healthcare Software can help by integrating data from various sources and supporting decision-making. In the future, AI could also improve prognosis accuracy and assist in selecting the most suitable treatment.
In a nutshell, this is the answer to the most asked question: “How Artificial Intelligence is Revolutionizing Healthcare Apps”. Artificial Intelligence is transforming healthcare applications, making medical imaging, patient monitoring, diagnosis, and treatment more efficient. From improving image accuracy in radiology to streamlining hospital workflows and enabling telemedicine, AI is shaping the future of healthcare. As technology advances, AI will continue to enhance personalized treatments, assist in drug discovery, and optimize healthcare operations. While challenges such as data privacy and regulatory approvals remain, the potential of AI in revolutionizing patient care is undeniable. The future of healthcare is AI-driven, bringing better outcomes for both patients and medical professionals.