Artificial intelligence in healthcare: transforming the practice of medicine PMC

AI for Healthcare: A Way to Revolutionize Medicine

A study conducted by Huang et al. where authors utilized patients’ gene expression data for training a support ML, successfully predicted the response to chemotherapy [51]. In this study, the authors included 175 cancer patients incorporating their gene-expression profiles to predict the patients’ responses to various standard-of-care chemotherapies. Notably, the research showed encouraging outcomes, achieving a prediction accuracy of over 80% across multiple drugs. In another study performed by Sheu et al., the authors aimed to predict the response to different classes of antidepressants using electronic health records (EHR) of 17,556 patients and AI [52]. The AI models considered features predictive of treatment selection to minimize confounding factors and showed good prediction performance. The study demonstrated that antidepressant response could be accurately predicted using real-world EHR data with AI modeling, suggesting the potential for developing clinical decision support systems for more effective treatment selection.

AI for Healthcare: A Way to Revolutionize Medicine

With continuously increasing demands of health care services and limited resources worldwide, finding solutions to overcome these challenges is essential [82]. Virtual health assistants are a new and innovative technology transforming the healthcare industry to support healthcare professionals. It is designed to simulate human conversation to offer personalized patient care based on input from the patient [83].

Precision medicine and clinical decision support

Therapeutic science repurposes already available drugs for other uses, and comes into play in scenarios such as public health emergencies where there is no time to develop a new drug from scratch. The sensors included in ordinary smartphones, augmented by data from personal fitness devices such as the ubiquitous Fitbit, have the potential to give a well-designed algorithm ample information to take on the role of a health care angel on your shoulder. The defendant challenged the sentence, arguing that the AI’s proprietary software — which he couldn’t examine — may have violated his right to be sentenced based on accurate information.

Fitzsimmons-Craft and her team are developing a chatbot to help guide people with eating disorders toward seeking care. “They’re just looking at the phrases and making predictions about what comes next.” So it’s important to use caution if you’re using them to seek health advice. Scientific articles that analyze the use of artificial intelligence in medical specialties. Early detection of certain mood conditions can be predicted by analyzing the trend, tone of voice, and speaking style of individuals. Prediction and assessment of a condition is something that individuals will demand to have more control over in the coming years.

Gathering clinician feedback at a growing practice

We are in the very early days of our understanding of AI and its full potential in healthcare, in particular with regards to the impact of AI on personalization. Nevertheless, interviewees and survey respondents conclude that over time we could expect to see three phases of scaling AI in healthcare, looking at solutions already available and the pipeline of ideas. AI is now top-of-mind for healthcare decision makers, governments, investors and innovators, and the European Union itself. An increasing number of governments have set out aspirations for AI in healthcare, in countries as diverse as Finland, Germany, the United Kingdom, Israel, China, and the United States and many are investing heavily in AI-related research.

AI for Healthcare: A Way to Revolutionize Medicine

In the form of machine learning, it is the primary capability behind the development medicine, widely agreed to be a sorely needed advance in care. Although early efforts at providing diagnosis and treatment recommendations have proven challenging, we expect that AI will ultimately master that domain as well. Given the rapid advances in AI for imaging analysis, it seems likely that most radiology and pathology images will be examined at some point by a machine. Speech and text recognition are already employed for tasks like patient communication and capture of clinical notes, and their usage will increase.

Multi-step, iterative approach to build effective and reliable AI-augmented systems in healthcare. Several measures must be taken to ensure responsible and effective implementation of AI in healthcare. Other diseases are caused by problems in how the cellular machinery reads DNA, a process known as epigenetics. Traditionally, a gene provides the recipe for a particular protein and joins molecules called transcription factors that instruct the cell how much of that particular protein to produce. When this process doesn’t go as planned, over or underactive genes lead to diseases like cancer, diabetes and neurologic disorders. This prompts scientists to search for solutions to restore the normal epigenetic activity.

AI for Healthcare: A Way to Revolutionize Medicine

There are numerous companies that are frontrunners in this area, including IBM Watson and Google’s Deep Mind. These companies have shown that their AI can beat humans in selected tasks and activities including chess, Go, and other games. Both IBM Watson and Google’s Deep Mind are currently being used for many healthcare-related applications. IBM Watson is being used to investigate for diabetes management, advanced cancer care and modeling, and drug discovery, but has yet to show clinical value to the patients. Deep Mind is also being looked at for applications including mobile medical assistant, diagnostics based on medical imaging, and prediction of patient deterioration [6], [7]. Advances in AI have the potential to transform many aspects of healthcare, enabling a future that is more personalised, precise, predictive and portable.

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AI for Healthcare: A Way to Revolutionize Medicine

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