Artificial Intelligence is powering every sector, and the healthcare industry is no exception. The healthcare industry is reaping the benefits of transformative data and triggering intense development in early detection systems, diagnosis, and monitoring of patients for enhanced healthcare delivery.
The global healthcare AI market was valued at $11 billion and is forecasted to reach $188 billion by 2030.
AI thrives on large volumes of healthcare data from care providers from hospitals, care centers, imaging and pathology labs, hospices, clinics, and more. The proper analysis of this data has an unlimited potential to transform human health, yet, the unorganized format of the data collected from dynamic sources renders it impossible for analysis and transformation.
Fortunately, the road to transformative healthcare is possible with innovation driven by AI and ML solutions.
Although AI can draw clinical insights from raw and unstructured data, developing advanced algorithms is still time and resource-consuming. However, with the pace with which the market is growing, it is plausible to expect AI-based healthcare solutions to provide unmatched benefits to medical professionals in different aspects.
Where AI and ML can Help Stimulate Better Healthcare Innovation?
Early Disease Detection
The promise of a better diagnostic process is one of the significant potentials of AI in healthcare applications. ML-based AI tools can be used to identify patients with detected and undetected common and rare conditions. Specialized ML tools will be able to interpret the data present in the Electronic Health Records, medical imaging, lab reports, and doctor notes of patients to ensure targeted early diagnosis conditions and predict the possibility of diseases. Early detection and diagnosis provide access to timely healthcare treatments, reduced treatment costs, and increased doctor-patient trust.
The promise of a better diagnostic process is one of the significant potentials of AI in healthcare applications. ML-based AI tools can be used to identify patients with detected and undetected common and rare conditions. Specialized ML tools will be able to interpret the data present in the Electronic Health Records, medical imaging, lab reports, and doctor notes of patients to ensure targeted early diagnosis conditions and predict the possibility of diseases. Early detection and diagnosis provide access to timely healthcare treatments, reduced treatment costs, and increased doctor-patient trust.Reliable Image Analysis
Imaging analysis is a critical aspect of medical analysis and treatments. However, doctors and medical professionals spend significant time performing repetitive yet critical tasks such as analyzing images, lab reports, and blood work.
With AI-assisted technology, doctors can reduce the time spent pouring over CT scans, Mammography, PET scans, MRIs, and more. They can leverage the potential of AI’s advanced pattern recognition capabilities to identify familiar features, established patterns, and early indicators of conditions and prioritize cases based on the diagnosis.
Enhanced Drug Discovery
One of the major revolutionary powers of AI is its ability to help design and produce valuable medicines to combat new and existing conditions. We need better solutions for the drug development process. It takes 12 years for a new drug to proceed from the research lab to the market and finally to the patient.With the help of advanced healthcare AI tools, it is possible to address the issues of drug discovery, repurposing, and pharmaceutical developments. AI can handle large volumes of critical data that aids in drug design, understanding chemical synthesis, identifying potential candidates, and analyzing drug-protein interactions.
AI’s capability to draw insights from historical drug data, biological datasets, and cross-reference formulas can be groundbreaking in potentially saving countless lives.
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The pandemic undoubtedly spurred innovation in telehealth, but there’s still a long way to go to make virtual visits as effective as physical visits to the doctor’s office.
AI can help close that gap in numerous ways. For example, machine learning and natural language processing (NLP) will help facilitate symptom collection using a patient’s voice.
Combined with an analysis of the patient’s electronic health record, AI can highlight potential health concerns for doctors to review. By processing information ahead of time, AI increases the volume of patients that doctors can handle, improves the efficacy of virtual visits, and even minimizes the risk of infection from physical interactions.
One of the major revolutionary powers of AI is its ability to help design and produce valuable medicines to combat new and existing conditions. We need better solutions for the drug development process. It takes Conclusion
Artificial Intelligence and Machine Learning are at the forefront of stimulating incredible changes and developments in the healthcare industry. At Shaip, we are at the crossroads of transformation for the healthcare industry. With our expertise in developing innovative and advanced AI-based tools, the future of the healthcare industry can provide better health for all.
We help organizations build, develop and deploy pioneering AI and NLP models trained on more than 10 million licensed medical data records. Our top-quality data sets are accurately annotated, ethically sourced collections of medical data from images, lab reports, physician speech, and EHR from diverse patient groups to ensure highly reliable outcomes.
We also have a deep understanding of AI from the ground up, so we can lend our experience in selecting unbiased cohorts, healthcare data annotation, and the demands of semi-supervised learning to ensure our clients’ success. For more information on the solutions Shaip can help put in place, please reach out and contact us today.
