Blogs
Welcome to our blog section on Artificial Intelligence (AI)! Here, we will explore in-depth one of the fastest and most exciting technological fields of the modern era.
Blogs
10/11/2023
Artificial intelligence has been utilized widely in the field of healthcare from answering patients’ questions to assisting doctors in hardcore tasks like detecting disease or even developing new pharmaceuticals. Why does AI is considered indispensable in the medical industry? Let’s dig dip into their benefits.
The artificial intelligence (AI) healthcare market has undergone significant growth in recent years. According to the reputable data and market analysis platform Statista, the market was valued at $11 billion in 2021 and is anticipated to skyrocket to an estimated value of $187 billion by 2030. This substantial surge in the AI healthcare market is set to catalyze remarkable shifts in the operations of medical providers, hospitals, pharmaceutical and biotechnology companies, and other stakeholders in the healthcare sector.
With multiple aspects, including more advanced machine learning (ML) algorithms, diversified accessibility to data, and more affordable software, the application of AI technology in doctors’ tasks has been increasing significantly. Artificial intelligence inventions could easily sift through enormous volumes of health data—from health records and clinical studies to genetic information—and analyze it much faster than humans.
Hospitals and healthcare departments are using AI to enhance the efficiency and effectiveness of all kinds of medical procedures, from back-office tasks to patient care. With the application of machine-learning algorithms, tasks from data analytics to diagnostics could be automated, enhancing the credibility, accuracy, and versatility of doctors’ work.
The following list are the examples of how AI could be used to benefit staff and patients:
Healthcare professionals dedicate a significant portion of their time to administrative duties and documentation. The integration of AI and automation emerges as a valuable solution, effectively managing these routine tasks. This technological advancement allows employees to allocate their time more efficiently, focusing on various activities while enhancing direct patient engagement. Notably, Generative AI in healthcare systems like smart data analytic software can assist clinicians by aiding in note-taking and content summarization, ensuring the meticulousness of medical records. Additionally, AI applications facilitate precise coding and seamless data exchange among different departments and billing processes.
Studies reveal that 64% of patients embrace the use of Generative AI in healthcare for continuous access to nurse support. Utilizing smart data analytics, AI-driven virtual nurse assistants, such as chatbots or dedicated applications, efficiently handle tasks like medication inquiries, forwarding reports, and scheduling physician visits. This technology significantly eases the burden on clinical staff, enabling them to prioritize direct patient care. Such advanced systems not only streamline healthcare data management but also ensure optimal electronic medical records management. They play a pivotal role in the Healthcare Information Systems (HIS), integrating seamlessly with the Hospital Dashboard for comprehensive healthcare data analysis.
Approximately 75% of severe harm resulting from diagnostic errors is attributed to overlooked vascular events, infections, and cancers. AI-based technology that specializes in disease detection could be used in this case to minimize the error in diagnosis, enhancing the accuracy of detecting diseases instantly and automatically.
In a recent study, 83% of patients highlighted inadequate communication as the most concerning aspect of their healthcare encounters, underscoring the pressing need for clearer patient-provider communication. Leveraging generative AI technologies such as natural language processing (NLP), predictive analytics, and speech recognition can significantly enhance communication efficacy within healthcare. AI implementation could provide more precise insights into patient treatment choices, empowering healthcare providers to engage in more meaningful conversations with patients and fostering collaborative decision-making for optimal care.
Harvard's School of Public Health suggests that AI integration in diagnoses could potentially reduce treatment costs by up to 50% and enhance health outcomes by 40%, although it's still in its early stages. One instance is seen in research conducted at the University of Hawaii, where employing deep learning AI significantly enhanced breast cancer risk prediction. Notably, the lead researcher highlighted the AI's capability to be trained on a larger image dataset than a radiologist, potentially spanning millions of radiology images, with minimal replication costs except for hardware expenses.
An MIT team developed a machine learning algorithm to discern the need for human expertise. In specific cases, such as identifying cardiomegaly in chest X-rays, a hybrid human-AI model yielded superior results.
In another study, AI showcased superior aptitude in identifying skin cancer compared to experienced doctors. Utilizing deep learning on over 100,000 images, researchers from the US, Germany, and France observed AI outperforming 58 international dermatologists in diagnosing skin cancer.
As health monitoring tools and apps gain popularity, more individuals rely on these technologies to track and analyze their health data. This real-time information can be shared with healthcare professionals, providing a comprehensive view of potential health issues. Additionally, advanced technologies like Generative AI in healthcare and healthcare assistant solutions play a pivotal role. These innovative systems contribute significantly to managing electronic medical records, alongside integration with the Hospital Dashboard, streamlining data accessibility and enhancing healthcare decision-making.
Utilizing AI in healthcare systems delivers a fundamental advantage by streamlining the collection and dissemination of information. AI plays a crucial role in enhancing the efficiency of patient data monitoring for healthcare providers.
Consider diabetes as an example. With approximately 10% of the US population affected by diabetes, patients now have access to wearable and other monitoring devices providing real-time feedback on glucose levels to both themselves and their medical teams. AI integration aids providers in the seamless collection, storage, and analysis of this patient-generated information. Harnessing AI's capabilities to process vast datasets allows healthcare professionals to derive data-driven insights from numerous individuals. This wealth of information empowers healthcare professionals to optimize disease treatment and management strategies for improved patient care.
Artificial Intelligence presents significant opportunities to reduce human error, support medical professionals and staff, and provide continuous patient services. As AI tools advance, their potential expands to encompass more extensive utilization in interpreting medical images, X-rays, and scans, diagnosing medical conditions, and formulating comprehensive treatment plans.
The applications of AI are poised to revolutionize a broad spectrum of tasks, encompassing call management, analysis of population health trends, and prospective unforeseen applications. It is foreseeable that future AI tools will automate or supplement a greater portion of clinical and staff responsibilities. This evolution will enable human resources to allocate more time to delivering efficient and compassionate face-to-face professional healthcare.
A WHO report has estimated that approximately 9.6 million cancer cases were recorded deaths in 2018, showing a deathly disease has been torturing innocent people day by day. Therefore, experts have suggested that early diagnosis is the current solution to improve the survival rate of patients.
In circumstances when the solution to overcome the consequences of cancer has not been found, Vinbrain, an artificial intelligence company that provides AI-based solutions for healthcare departments, has built up early and accurate cancer detection.
DrAid™ CT Liver Cancer D&T and DrAid™ MRI Rectal Cancer D&T, the two AI that owned by Vinbrain, served as a machine-learning technology for cancer detection. These artificial intelligence in healthcare systems is designed to assist radiologists in automatically detecting abnormal lesions through CT imaging and MRI, provide clinical solutions to aid in the early identification of cancer, as well as assist oncologists in developing treatment plans.
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