Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare. A Read You Need, Inspired by Accenture!
According to an analysis by Accenture, key clinical health AI applications can offer US healthcare economy the advantage of $150 billion in annual savings by 2026. AI is empowering healthcare at various levels by enabling machines to sense, comprehend, act and learn, so machines can perform administrative and clinical healthcare functions on their own.
AI is growing with an immense potential to unleash tangible benefits in cost, quality and access. AI market is expected to reach $6.6 billion by 2021, which accounts 40 percent annual growth rate. Considering the increasing demand for artificial intelligence AI, many mobile app development companies in Saudi, Dubai, New York, Bangalore and London have widened their service portfolio with AI services.
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The Accenture’s analysis highlighted 10 AI applications, and according to analysis, these applications have the greatest near-term impact in healthcare.
Top 10 Healthcare AI Applications and the Total Values They Could Have By 2026
- Robot Assisted Surgery – $40B
- Virtual Nursing Assistants – $20B
- Administrative Workflow Assistance – $18B
- Fraud Detection – $17B
- Dosage Error Reduction – $16B
- Connected Machines – $14B
- Clinical Trial Participant Identifier – $13B
- Preliminary Diagnosis – $5B
- Automated Image Diagnosis – $3B
- Cybersecurity – $2B
Benefits of AI in Healthcare
- Improve Workforce Productivity: AI can fill the gap of the rising labor shortage in healthcare. Artificial Intelligence AI has the power to reduce burden on clinicians and give staff the ability to do their job more effectively and efficiently.
- Institutional Readiness: Healthcare organizations can implement AI in formulating their organization’s structure and governance. Artificial Intelligence AI-smart workforce and culture help enhance efficiency, quality and results.
- Patient Care: AI can improve patient care by integrating health data across platforms. With access-ready data that can be accessed from anywhere, any device, doctors can understand disease well before that get aggravated.
- Using Robot to Explain Lab Results: AI-powered robo can interpret lab results, including blood tests and genetic tests and deliver results that are easy to analyze and understand.
- Emotional intelligence indicators: AI-based virtual assistants are heavily in use today. They are being made emotionally intelligent with natural language processing technology, so they can understand user behaviour better.
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30+ Examples Of Ai In Healthcare That Will Make You Feel Better About The Future
Using ai to efficiently diagnose and reduce error
- More accurate cancer diagnosis with ai
- An intelligent symptom checker
- Ai deep learning for actionable insights
- Earlier cancer detection with ai
- Diagnosing deadly blood diseases faster
- Ai-powered radiology assistant
Developing new medicines with ai
- Ai in biopharmaceutical development
- Treating rare disease with ai
- Ai, cloud-based digital drug discovery
- Neural network for clinical trials
- Finding better candidates for developmental drugs
- Deep learning for targeted treatment
Streamlining patient experience with ai
- Automating healthcare’s most repetitive processes
- Real-time patient flow optimization
- Increasing access to healthcare
- Using machine learning for a better patient journey
- Personalized healthcare plans with ai
- Faster hospital visits, courtesy of ai
Mining and managing medical data with ai
- A massive data library for personalized health
- Ai for hospital risk prediction
- Looking at the data behind the medical image
- Ai for data throughout the health system
- Watson’s side gig helping hospitals
- Alerting doctors when patient’s are in trouble
- Data and the ‘digital life’
Ai robot-assisted surgery
- Virtual reality-enabled robotics for surgery
- Ai robots revolutionizing endoscopy
- Precision robotic treatment for treating cancer
- Pioneering robotic surgery
- Robot-facilitated heart therapy
- Improving surgical precision
- Spinal surgery with robotics & ai
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How is artificial intelligence used in the medical field?
Let’s look at each of these amazing use-cases in more details.
- Clinical decision support
- Information Management (both physician and patient)
How is AI used in pharma (executive summary)?
- Mobile coaching solutions
- Personalized medicine
- Acquisitions
- Drug discovery
Know the current limitations of AI in healthcare
- Initial adoption issues
- Data privacy concerns
- Compliance to regulations
- Black box difficulty
- Stakeholder complexities
- Clinical decision support
- Easy to use with a clear output
What are some applications of artificial intelligence systems in healthcare?
- Aidoc/MaxQ – CT brain bleed diagnosis
- IDx-DR – Detect signs of diabetic retinopathy
- iCAD – Breast density via mammography
- QuantX – Breast Lesions
- Zebra Medical – Coronary calcium scoring
- Bay Labs – Echocardiogram EF determination
- Neural Analytics – Device for paramedic stroke diagnosis
- Icometrix – MRI brain interpretation
- Imagen OsteoDetect – Wrist fracture detection in adult patients
- Viz.ai – CT stroke diagnosis
- Arterys – Liver/lung cancer (MRI, CT) diagnosis and MRI heart interpretation
- Mayo Clinic – AI cervical cancer screenings
- DeepMind – Eye disease detection
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Conclusion:
AI is changing the way how businesses operate and deliver results. The healthcare industry is one of the key industries that is leveraging AI to improve workforce productivity, enhance patient care and deliver true results. If you’re on the urge of leveraging AI, you’re suggested to collaborate with an expert AI app development company or mobile app development company who has deep understanding of AI concepts like Power BI, machine learning, deep learning, NLP, and NLU.
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