Artificial Intelligence (AI) is changing how the healthcare industry functions in unimaginable ways. It is transforming every step of the healthcare process, from research to assisted care and everything in between. Let’s explore 12 ways in which AI is massively revolutionizing the healthcare industry for good.
Drug Discovery and Development
The traditional drug discovery and development process is incredibly time-consuming and expensive. Fortunately, this process can now be faster with AI. This tech can be used in different parts of drug discovery processes, like drug screening, drug design, polypharmacology, chemical synthesis, etc., speeding up drug discoveries and development. It will accelerate the pace of introducing newer, effective drugs to the public, helping them cure diseases/illnesses faster.
Virtual Nursing Assistants
Some senior citizens and people with disabilities (especially mobility issues) find it difficult to physically visit hospitals/clinics for routine check-ups due to their health challenges. The healthcare sector has taken note of this situation and turned to virtual nursing assistants to serve such patients. Virtual nursing assistants are breaking accessibility barriers by providing health monitoring, consultation, treatment reminders, etc., virtually. You can expect more health organizations to adopt virtual nursing assistants to serve more patients, improving their quality of life.
Clinical Decision Support
Doctors have long relied on traditional tools like MEWS to calculate the risk for clinical deterioration in patients. While it was always an effective tool that helped doctors approach clinical deterioration proactively, AI is now replacing it for faster and more accurate decision-making. While various approaches to incorporating AI into clinical decision-making exist, AI-CDS is the most common. It refers to integrating AI models into clinical decision support (CDS) systems to identify kids at risk of specific diagnoses or clinical deterioration early. It has lowered false alerts and missed patients, improving the service quality.
Telemedicine
Telemedicine bridges the doctor-patient gap by using AI to take healthcare services virtually. Patients living in rural areas or locations with limited healthcare facilities can now connect to doctors via video calls, phone calls, etc., for accurate diagnosis, consultation, remote health monitoring, and much more. This process is gaining popularity because it saves patients’ and doctors’ time, reduces treatment costs, and makes good healthcare accessible to everyone.
Medical Imaging
Medical imaging is a critical aspect of clinical analysis and diagnosis because it creates visual representations of your body’s interiors. While the traditional medical imaging approach was effective, it wasn’t fast and accurate. This is why AI is now being used to analyze and interpret data generated by medical imaging techniques like CT scans, X-rays, MRIs, etc. It helps doctors identify complex patterns and features that human eyes may miss. As a result, doctors can now detect early-stage diseases and provide timely interventions to save people’s lives.
Automating Administrative Workflow
Healthcare workers employed for administrative tasks juggle multiple responsibilities, leading to faster burnout. Hence, the industry now integrates AI to automate repetitive tasks to free up employees’ time. Automating processes like patient scheduling, patient admission, assigning patient calls to the right person, maintaining EHR systems, managing staff roster, etc., can improve the overall operational efficiency and enable administrative workers to serve patients better.
Predictive Analysis
The ability to precisely predict patient outcomes is crucial in the healthcare sector. Traditional risk assessment methods often fail to grasp the dynamic nature of patients’ conditions. This is where AI-driven predictive analysis comes into the picture. AI predictive analytics uses advanced machine learning techniques and algorithms to analyze vast patient datasets. It helps by identifying patterns and correlations within the datasets to generate predictive models that can accurately forecast patient outcomes. These models can help doctors provide timely and effective interventions.
Robotic Surgery
Surgeries were one area exclusively reserved for human surgeons, but the healthcare sector is slowly opening up to the idea of robots conducting certain surgeries. Also known as robot-assisted surgery, these systems can perform delicate yet complex procedures with precision that were otherwise impossible or too difficult to conduct using other methods. While the idea of robots conducting surgeries can appear risky, they are performing well. They result in fewer complications, less pain, less noticeable scars, less blood loss, etc., making them a viable solution.
AI in Genomics
The blend of genomics (the study of genes) and AI is making medicine more predictive, personalized, and preventive than ever, especially for terminal conditions like cancer. It aids the identification of cancer subtypes, better knowledge of cancer-driving genes, discovery of new markers, etc., facilitating personalized treatment.
What makes AI-driven genomics truly pathbreaking is its ability to monitor the patient’s gene data over time and track genetic makeup’s response to current treatment. This information helps doctors adjust treatments for optimal outcomes, leading to faster recoveries.
Diagnostic Support
The volume of medical data generated regularly is massive and cannot be analyzed by even large teams of human practitioners. However, AI models can easily analyze these datasets to identify patterns and correlations that human eyes can easily miss. It has resulted in early disease detection, facilitating timely prevention and personalized treatments. The best part of using AI in diagnostic support is its accuracy and speed, which contribute to more reliable diagnoses.
AI-Powered Chatbots
The integration of AI-powered chatbots in healthcare organizations is the biggest step towards making healthcare accessible to everyone. These chatbots use sophisticated algorithms, NLP, etc., to comprehend every user’s request context and provide the most relevant and accurate response.
Since the responses are automated, people can receive answers to their questions even during odd hours, providing relief and assistance at any time. Besides answering questions, these chatbots can provide personalized health information and facilitate better doctor-patient communication for optimal experiences.
Enhanced Medical Research
One of the most notable ways in which AI is changing the healthcare sector is by upgrading medical research for faster drug discoveries and other research. For example, healthcare researchers use AI to analyze data from several observational and clinical trials to make inferences about the effectiveness and safety of drugs being evaluated. They’re also used to improve clinical trials’ conduct, augment operational efficiency, aid site selection, etc. All this supports researchers at varying research steps, making their work much easier than before.
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