AI in Healthcare: And therefore revolutionizing how we diagnose, treat, and care for patients.

Introduction

With the combination of artificial intelligence (AI) technologies, healthcare is going big time. AI can be a game changer in all areas around healthcare, from improving the accuracy of diagnoses to providing personalized treatment and improving patient care. Innovation around AI at an unprecedented pace are driven by the potential of AI to both accelerate drug discovery, reduce human error and improve patient outcomes.

This article is a review of how AI is reshaping healthcare in different fields, such as diagnostics, drug discovery and patient care, as well as how AI in healthcare raises some important ethical considerations.

1. Medical Imaging and Diagnosis using AI

Medical imaging has been powered by AI to empower healthcare providers to quickly and effectively diagnose diseases. And powered by deep learning algorithms, AI is able to dig for insights in complex medical images – x rays, MRIs, CT scans – quicker than conventional methods.

Increase the speed and Accuracy of Diagnoses.

Doctors can use the AI-powered tools to spot patterns and anomalies in medical images thereby, having the early detection of diseases such as cancer, cardiovascular issues, or neurological disorders. In seconds, these algorithms can tell when something is abnormal and where 'yes there is a tumor right there,' so radiologists can make more precise diagnoses.

Example: AI tools, from a company like Zebra Medical Vision or Arterys, are being used to look through radiology images for signs of breast cancer, lung disease or even brain aneurysms; sometimes detecting the problem even before it becomes symptomatic.

AI in Early Cancer Detection

AI in detection of cancer at early stages is one of the most impactful ways AI is being used in healthcare. Early signs of cancer in mammograms, and other imaging modalities, can be identified by machine learning algorithms in machine learning algorithms, and the resulting early treatment will improve survival rates significantly.

Example: An AI system created by Google's DeepMind can spot breast cancer with greater precision than human radiologists, cutting down the number of false positives and negatives.

2. During completion of this dissertation, the focus will be on the use of AI in Drug Discovery and Development.

The traditional process of drug discovery has been long, expensive and complex. But it's now being revolutionized by AI, which can find potential drug candidates, predict molecular behaviors, and even optimize clinical trials in a fraction of the time it used to.

Accelerating Drug Discovery

With a database of billions of molecular structures at hand, AI algorithms are capable of sifting through to find promising combinations of chemical compounds capable of fighting specific diseases. That helps cut the time it takes to get new drugs to market and meet unmet medical needs quicker.

Example: Deep learning is the tool Atomwise, an AI drug discovery company, uses to predict how different drugs will interact with a given disease, identifying new compounds to treat disease.

AI in Precision Medicine

The drugs have also been made using AI to create personalized drugs that can be matched to the genetic profiles people have. AI can analyze genetic data to come up with more effective medications for certain patient populations, cutting down on adverse reactions and improving the rate of successful treatment.

Example: Immunotherapies are personalized treatments that use the body’s immune systems to fight diseases such as cancer and are already in use; AI has been key in developing such treatments.

3. Personalized Medicine with AI

Another area where AI is progressing rapidly is into personalized medicine. Using a patient’s genetic information and lifestyle as well as their medical history, AI algorithms can formulate better treatment plans that are custom made to that patient, rather than one size fits all.

Genomics and AI

AI has dramatically improved genomics by identifying the genetic mutations that cause diseases, and predicting how patients will respond to treatment. This enables doctors to build more focused treatment strategies fashioned against each person's genetic profiles.

Example: By analyzing large sets of genetic data, IBM Watson For Genomics can recommend personalized cancer treatment options promising better patient outcomes.

Predictive Healthcare

Predictive AI models will be able to tip which patients are going to develop certain diseases, based on their medical data. It enables doctors to suggest lifestyle changes or screen for early signs of disease.

Example: With the help of AI, Benevolent AI can predict the chance of disease progression, and therefore, doctors can plan prenatal care in advance and prevent hospital readmissions.

4. In Patient Care and in Virtual Assistance – AI

Virtual assistance and remote monitoring are enhancing the quality of patient care, besides transforming the diagnosis and treatment using AI. With the help of AI chatbots, telemedicine platforms and wearable devices, healthcare is becoming more accessible and convenient for people suffering from chronic health disorders.

AI in Telemedicine

AI is being used on telemedicine platforms to enable virtual consultation and render patients with medical solutions while remaining in their homes. But AI can help, too, by allowing AI driven chatbots to handle routine inquiries such as scheduling appointments or giving medical advice so that health care providers can focus on more serious business.

Example: Babylon Health uses AI to offer consultations, providing you medical advice in real time and connecting you to doctors if they are needed.

Chronic Disease Management and Remote Monitoring

Today it has become common knowledge that wearable devices (like smartwatches and fitness trackers) integrate AI algorithms to monitor vital signs and alert abnormalities on the fly. It helps doctors get a handle on chronic conditions, like diabetes and heart disease.

Example: Now the Apple Watch has an AI powered Electrocardiogram (ECG) feature that tracks irregular heart rhythms so you know about issues with your heart in its beginning stages.

5. This thesis covers the ethical considerations and challenges in the design of artificial intelligence technology (AI) in the context of healthcare.

Despite its massive potential to transform healthcare, AI also presents serious ethical questions. As AI is increasingly being incorporated into healthcare systems, various issues including patient data privacy, algorithmic bias, and role of AI in substituting human healthcare workers have to be taken into account.

Data Privacy and Security

Because AI systems depend so heavily on large amounts of patient data, there are major concerns about both data security and patient privacy. AI systems must conform to regulations such as HIPAA (Health Insurance Portability and Accountability Act) to make sure sensitive patient info is secure.

Finally, I explore Algorithmic Bias in AI healthcare tools.

The data the AI system train upon is only as good as the AI system. When used without analyzing further whether its training data was biased or incomplete, AI algorithms can produce biased algorithms which produce biased results that exacerbates disparities in healthcare outcomes.

Example: Biases have been shown in some training data that were then interpretable in some AI driven diagnostic tools that actually performed unfairly on minority populations.

Impact on Healthcare Jobs

This also gives way which leads AI to replace some of the tasks traditionally done by healthcare workers and this cause the concerns that all these will displace the job. Yet, AI has also launched new opportunities for human and machine working together where AI does work to support how healthcare providers do theirs.

Conclusion

The healthcare industry is getting transformed with artificial intelligence, providing new ways to diagnose, treat and provide care for patients. How can AI help? AI applications in healthcare range from AI powered medical imaging, a more personalized medicine, to telemedicine: all together contributing to more efficient, more accurate, and more accessible healthcare. Nevertheless, as AI finds its way into healthcare, it’s important to raise questions of ethics, especially to make sure that AI technologies are as helpful to all the patients as they can be.

Increasingly, as AI evolves, AI will help healthcare develop and determine patient outcomes and deliver more efficient and personalized treatments.