The Role of Artificial Intelligence In Healthcare

AI is becoming a critical element of healthcare systems, changing the approach in medicine toward precise and highly effective methods and, in general, creating a hopeful future for people’s health. Now, let’s understand how and where AI transforms diagnosis and treatment, management, and admissions in healthcare.

AI Diagnostics In Healthcare

A survey conducted by Accenture in 2023 established that 83% of health executives saw AI delivering potentially radical, timely change in their organizations in the next three years. A survey conducted by PwC in 2017 pointed out that 72% of healthcare industry actors now implement and plan to implement AI in their activity. Here’s a look at AI Diagnostics in healthcare:

  • Medical Imaging Analysis: The analytical reports are created using big data sets of medical images (several types of visual tests, including X-ray, MRI, and CT). For example, a study published in Nature shows that an experiment achieved 95% accuracy by an AI system for the classification of mammograms compared to a radiologist. 
  • Predictive Analytics: The analysis aims to diagnose various diseases by explaining the patient history, blood, tests, and genetic information about hazardous disease risk factors. A 2020 research paper in The Lancet showed how AI models could use data within the EHRs to predict which patients would develop heart failure with an accuracy level of 73%. 
  • Virtual Assistants and Chat bots: A typical application of AI in healthcare is a chatbot that allows the answering of patient questions and appointment booking besides symptom diagnosis. A JMIR study revealed that through the utilization of chatbots, patients’ waiting time was well addressed, as was the case with the efficiency of the appointments.
Feature Benefit Example
Medical Imaging Analysis Improved accuracy and earlier detection of diseases AI can detect subtle abnormalities in mammograms that human radiologists might miss.
Predictive Analytics Proactive identification of at-risk individuals AI can predict patients susceptible to heart failure based on medical history data.
Virtual Assistants & Chatbots Enhanced patient engagement and access to information Chatbots can answer basic health questions and streamline appointment scheduling.

Table 01: Impact of AI on Diagnostics

AI Applications In Treatment

  1. Surgical Robotics: Robots are being used in operating rooms to help surgeons in minimally invasive surgeries as this reduces mistakes. A 2021 research in Surgical Endoscopy provided that robotic operation for colonic cancer enabled less bloodshed and shorter lengths of hospital stays in comparison with conventional methods.
  2. Personalized Medicine: AI helps in profiling the patient, suggesting what kind of treatment the patient needs, and the correct dosage of the drug. An article published in Nature Medicine in 2023 showed that AI can predict the individual genetic characteristics of cancer patients to determine the best response to certain drugs.
  3. Patient Recovery Management: It can continuously assess patients’ conditions, observe their status changes, and record any complications after release. A paper from 2022 in the journal JMIR discussed how, through remote monitoring systems and AI, patients were more compliant with their medications, and the hospital readmission rate was decreased.


Feature Benefit Example
Surgical Robotics Increased precision, reduced complications Robotic arms assist surgeons in minimally invasive procedures, leading to faster recovery
Personalized Medicine Tailored treatment plans and drug dosages AI can predict how patients respond to specific medications based on their genetic makeup.
Patient Recovery Management Improved post-discharge monitoring and outcomes AI systems can remotely monitor patients after surgery, detecting potential complications early.

Table 02: Impact of AI on Healthcare Treatment

AI Applications in Healthcare Management

Applying artificial intelligence in hospitals can help make the best decisions concerning the distribution of resources.

  • Resource Allocation: Research conducted in Health Affairs in 2020 demonstrated the efficiency of AI-based systems in bed management regarding the actual problems of increased non-scheduled stays and the increase in admission times of patients in emergency departments.
  • Administrative Tasks: AI is used in repetitive office tasks like appointment scheduling, managing electronic health records (EHRs), incoming document handling, and coding medical bills. A 2023 report by McKinsey & Company identified that AI could automate up to 80% of clerical work in healthcare, saving admin staff’s time.
  • Fraud Prevention: It can also analyze billing data and recognize instances of fraud. According to a March 2022 Journal of Medical Economics study, implementing an AI-based system can save healthcare organizations millions annually on fraud detection expenses.


Feature Benefit Example
Resource Allocation Optimized utilization of hospital resources AI can predict patient bed occupancy and allocate resources efficiently.
Administrative Tasks Increased efficiency and reduced costs AI can automate tasks like scheduling appointments and managing electronic health records.
Fraud Prevention Improved financial integrity and cost savings AI can detect fraudulent billing activities within healthcare systems.

Table 03: Impact of AI on Healthcare Management

AI Faxing in Healthcare Management

AI is fast transforming the different facets of healthcare. Traditional faxing is still prevalent. Still, it is possible to enhance the utilization of faxes through AI faxing.

Streamline healthcare operations and patient care with Phelix’s Fax AI Inbox. It automates fax processing, freeing up administrative staff for more critical tasks. Phelix can extract data from faxes with over 90% accuracy, eliminating the need for manual data entry. Additionally, Phelix offers insightful analytics at the user or fax level, empowering data-driven decision-making. Here’ how Phelix’s Fax AI Inbox works:

  1. Automatic Fax Intake: Phelix’s Fax AI Inbox automatically fetches faxes from your existing fax service or the shared directory, so you do not need to upload them manually.
  2. Multi-Page Handling: Phelix’s Fax AI Inbox can work with faxes containing many pages. It recognizes a cover page as the first page and, if presented with it, extracts the needed data from the following pages.
  3. Document Classification: Faxes delivered to the system are then classified into categories such as referrals or prescriptions, among other things.
  4. Data Extraction: Phelix’s Fax AI Inbox extracts fax details such as patient details, diagnosis, from and to providers, insurance, urgency, encounter dates, referral dates, etc.
  5. User Review and Correction: Users can edit the extracted data and even make more corrections on the same before it is input for storage in the system.
  6. Templated Responses: Templated messages can be sent for various use cases like missing information or auto replies.
  7. Medical Record Integration: Phelix works in conjunction with your Electronic Medical Records system to handle tasks and data directly from the faxes.

Book a demo today and see how it can help you or your organization achieve higher efficiency, cost savings, and exceptional patient care.

Ethical Considerations & Challenges Of AI In Healthcare

There are some serious obstacles to deal with, such as:

  1. Data Privacy: Applying AI in healthcare challenges patient data privacy. Security is a significant factor in protecting confidential information and preventing penetration by the wrong elements.
  2. Cost of Implementation: While the adoption and management of some AI systems could be costly, advanced AI faxing solutions like Phelix provide healthcare facilities with an affordable initial entry point into AI-integrated workflows.
  3. Human Oversight: Something as complex as AI must be considered an extension of human intelligence and beyond. Clinicians must have final decision-making rights while employing the outcomes derived from AI tools.

The Future of AI in Healthcare

Let’s uncover the extremely promising potential of AI in healthcare.

  • Personalized Treatment Plans: AI will extend treatment options by adapting them to patients’ genetic profiles and medical backgrounds.
  • Remote Patient Monitoring: AI applications in remote monitoring will further advance, thus allowing ongoing patient support outside the hospital.
  • Drug Discovery: It will utilize the capability of big data to extract relational information about biological systems in response to discovering new drugs and treatment realities.
  • Affordability and Accessibility: With advancements in the use of Artificial Intelligence in technologies, subsequent versions of AI solutions will be cheaper and consequently expand healthcare services to the far reaches of the world.

The Final Note

Healthcare is one of the most critical sectors embracing artificial intelligence.  The sector has also been enhanced because AI can be applied to interpret images for disease diagnosis and devise treatment methods based on the patient’s history. Nevertheless, problems related to data protection, algorithm bias, and cost persist and should be worked on. As numerous research studies continue, artificial intelligence is bound to take even more prominent positions in determining new paradigms of a healthcare system with more tailored approaches, open access to care, and, therefore, better quality of life.

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