AI in Healthcare: Changing the Way Diagnosis and Treatment is Done

Introduction

Artificial Intelligence (AI) is having a dramatic effect on industries worldwide, and healthcare is proving one of the most potentially rewarding sectors for AI application. AI is transforming the delivery of healthcare to patients—from diagnosis of diseases, to personalizing treatment, to discovering new drugs.

In this post I will address the cutting edge applications of AI in healthcare ranging from diagnostics, personalised medicine to drug discovery, virtual health assistants, and the ethical issues in AI. The idea of AI is not some far off fantasy, and it is already helping improve patient outcomes and streamline healthcare services.

1. Machine learning, Artificial intelligence, and deep learning are buzzwords in the medical imaging world.

As AI powered diagnostic tools change the way diseases are caught and treated. Medical imaging is one of the areas where AI have promised most in terms of machine learning algorithms being able to detect diseases with high accuracy from medical scans such as X rays, MRIs and CT scans.

How AI Enhances Diagnostics

Generally, diagnosing diseases from medical images was a time consuming process that required radiologists with necessary training to conduct manual interpretation of the results. Yet, these images can now be analyzed by AI algorithms to see potential abnormalities in seconds. AI systems have shown remarkable success in identifying conditions such as:

• Cancer: They show that AI can detect early stage tumors that may not be detected by a human eye.
• Cardiovascular Diseases: AI models can use the predicted readout from cardiac images to predict whether a heart attack or a stroke is going to happen.
• Neurological Disorders: Brain scans can now be scanned for signs of Alzheimer’s and Parkinson’s disease, thanks to AI tools.
• Example: AI algorithms built by researchers can detect breast cancer from a mammogram better than human radiologists a second set of eyes for early detection.

AI’s fast, accurate processing of large amounts of data is revolutionizing diagnostics — enabling faster, more precise treatment decisions.

2. Personalized Approach to Treatment with AI

The shift towards personalized medicine via AI is paving way to treatment that is specifically tailored to that patient based on their own health data. AI analyzes patient records, genetic information and even real-time health data going through wearable devices and recommend treatment plans designed specifically for every person.

In this episode of the Future Podcast I discuss how AI can personalize healthcare.

• Genomic Data Analysis: Through the genetic makeup of the patient, AI allows physicians to predict how a patient may respond to certain treatments. In cancer at least, where particular genetic mutations are driven by targeted therapies, this is especially important.
• Predicting Patient Outcomes: Doctors can use AI algorithms to help in predicting how a patient will respond to a specific treatment; using those predictions, doctors can choose the best therapy with the fewest side effects.
• Optimizing Treatment Plans: Using the patient’s changing health data, AI can make suggestions for changing treatment plans. This is very helpful for chronic diseases, like diabetes or heart disease.

Example: Oncology is using AI to pair cancer patients with the best treatment option, based on their genetic profiles, and survival rates are higher.

The future of personalized healthcare delivered on-demand through AI is paving the way for what we will no longer see in our world — one size fits all approaches to medicine.

3. Investigates the use of AI in Drug Discovery and Development.

New drugs can take years to develop and billions of dollars. But AI is streamlining this process by quicker, more efficiently fingered potential drug candidates than traditional methods.

AI's Role in Drug Discovery

• Analyzing Biological Data: With tremendous data from biological experiments, clinical trials, or research papers, vast amounts, AI can identify compounds that can potentially be effective against an ailment.
• Predicting Drug Interactions: Such AI models can make estimations (predictions) of how new drugs will interact with the human body and whether that will lead to some adverse side effects.
• Speeding Up Clinical Trials: Pharmaceutical companies use AI to design more efficient clinical trials through identification of the best drug testing candidates.

Example: One major help from AI was in the side of identifying treatments for COVID-19 by evaluating existing antiviral drugs and predicting which would likely be effective towards the virus.

AI helps researchers find new treatments faster and cheaper as way to fight diseases such as Alzheimer’s, Parkinson’s and cancer, delivering hope to millions of patients.

4. We put forward AI powered Virtual Health Assistants.

Virtual health assistants and chatbots powered by AI are becoming a welcome resource in and out of the exam room. These are health tools meant to help patients take charge of their health, receiving answers to questions and scheduling appointments, and even giving medical advice according to the symptoms.

The ways in which AI Virtual Assistants Enhance Patient Care

• 24/7 Access to Healthcare: AI chatbots help patients gain access to healthcare advice and support on any time of day, preventing unnecessary doctor visits.
• Remote Patient Monitoring: AI devices and apps can help watch how people with chronic diseases, like diabetes or hypertension, are doing, and tell healthcare providers if they are getting worse.
• Telemedicine Integration: As telemedicine has become common, AI assistants enable doctors to corral virtual appointments, track patient progress and suggest further action.

Example: The AI-based app, Babylon Health lets users input their symptoms with a guarantee of instant medical advice. It also enables doctors monitor remotely patient health metrics.

To solve the gap between patients and healthcare providers, AI assistants have come to help with better accessibility and the most efficient access to it.

5. The Ethics and Challenges of AI in Healthcare

As with any disruptive technology, AI in healthcare brings with it several ethical and practical challenges that must be addressed:

1. Data Privacy and Security

However, most AI systems need a massive amount of patient data in order to work properly. It’s important this data is secure and ethical. Questions remain about how patient data is stored, accessible by whom and how it is used.

2. Algorithm Bias

The data that AI models are trained on is only as good as the AI can receive. But if the training data is biased, the decisions the AI system makes will be biased, and can affect patient outcomes. For instance, an AI system trained mostly on data from white patients might not work as well at diagnosing diseases in minority populations.

3. Healthcare Systems Integration

Introducing AI technologies into existing healthcare systems will not be an easy ride. There’s not the infrastructure in many healthcare providers to support advanced AI tools, doctors may need more training on how to use these tools properly.

Healthcare stands to hugely benefit from AI, but we must address these challenges in order to ensure that everyone benefits equally from the technology.

Conclusion

In healthcare, AI is powering a revolution, from diagnosis of diseases to personalized treatment to each patient. AI in drug discovery, medical imaging, or patient care is already improving outcomes, or saving lives. Yet, the advancement of AI necessitates addressing the ethical and practical challenges in order to avoid being used in a responsible and effective manner.