6 Outstanding Applications of AI in Today’s Care Ecosystem
Behold the Magic of Intelligent Care Healthcare with Artificial Intelligence
Artificial intelligence (AI) – the smart, cognitive devices of today’s era – has penetrated extensively across all possible verticals – from financial services to manufacturing – and healthcare is no exception. With interest in AI booming exponentially, its scope of application in care-based applications has widened beyond imagination.
Reports indicate that the AI-driven healthcare market will see a tremendous growth of almost 40% by the end of this decade. From delivering advanced care-related information to physicians to make informed decisions to personalized real-time treatment, advanced applications of AI in healthcare are indeed revolutionizing care.
Let’s check out some of the outstanding applications of AI in today’s care ecosystem.
1. Diagnosis
One of the most advanced applications of AI in healthcare is in disease diagnosis. With AI, machines are supercharged with the ability to analyze voluminous data from medical images, prompting early diagnosis of many disorders. AI provides an easy solution through intelligent diagnostic imaging. This approach has multiple applications in proactive diagnosis of the possibility of stroke, tumor growth, and certain types of cancer, giving the physician the chance to derive a comprehensive treatment plans for patients well ahead of time.
2. Biomarkers
Biomarkers automatically provide accurate visual and audio data of patients’ vital health parameters that indicate the presence of specific medical conditions, help choose the ideal medications, or assess treatment sensitivity. Biomarkers accurately capture symptoms, as against the guesswork of symptoms perceived by patients. The accuracy and speed of biomarkers have made them the preferred tools of diagnosis, promptly highlighting possibilities of any disorders.
3. Virtual nursing assistance
AI -based applications and chat bots support care providers in delivering nursing assistance after discharge from hospital. This feature helps simplify provision of outpatient services and increases the accuracy of monitoring patient compliance post discharge. Available even as simple wearable’s and on smart phones, these AI-enabled devices also act as virtual health assistants that remind patients about their medications, encourage them to follow their exercise routines, answer simple medical clarifications sought by patients, and warn care providers about any untoward incidents such as sudden increase in blood pressure or a fall.
4. Remote monitoring of patients
This involves round-the-clock remote monitoring of patients, constant evaluation of their vital signs, and real-time alerts to caretakers and care providers. This remote assessment of vital health parameters helps physicians identify core symptoms of diseases and disorders in patients and respond accordingly. This approach clearly prevents unnecessary visits to the physician to a great extent.
5. AI and drug discovery
AI-driven computing can accurately and promptly study structures of multiple drug molecules and predict their pharmacological activity, potency, and adverse effects. This possibility opens up a rapid and cost-efficient route of drug discovery. It also has the chance of drastically reducing the cost of medications. Used across pharmaceutical companies, AI-based drug discovery has contributed to supporting the treatment of cancer and neurodegenerative disorders.
6. AI-enabled hospital care
AI simplifies care delivery in hospitals through a wide range of solutions including smart monitoring of IV solutions, patient medication tracking, patient alert systems, nursing staff performance assessment systems, and patient movement tracking within hospitals. Robot-assisted surgeries and AI applications in routine phlebotomy procedures are other potentially useful applications. AI has been found to considerably decrease dosage errors and increase nursing staff productivity in hospitals.
Conclusion – the era of AI has arrived in style
With voluminous investments pouring in for AI applications in healthcare, this technology still has a long way to go, despite its presence in healthcare for quite many years now. The main reasons for its slow adoption are the cost of research, the security concerns involved in opening up extensive databases, and misconceptions or errors in coming to quick conclusions. But the quest for ideal AI solutions looks quite promising indeed, with AI supplementing healthcare and improving the quality of care from diagnosis to prognosis.
So, where are you in your journey towards an AI-driven care ecosystem?