7 Healthcare Industries Ready to be Disrupted by AI 2022

1. OSP 7 Healthcare Industries Ready to be Disrupted by AI 2022

2. Index 01 Introduction 1 02 AI in Medical Diagnosis 2 03 AI in Medical Billing 4 04 AI in Pharma 6 05 AI in Medical Imaging 8 06 AI in IoT 10 07 AI in Pathology 12 08 AI in Radiology 14

3. Introduction The achievements of AI by 2022 may resemble a futuristic science fiction novel, but AI is rapidly reshaping our present, and making these fictional ideas into reality. In this eBook, we have identified seven healthcare sub-industries that will see a great impact and massive transformation in the coming years. Their current challenges, an overview of AI-based solution workflow process, the modules, interesting use cases, and finally, the benefits are discussed in detail. Our humble effort is to examine the progress and adoption of AI across different healthcare sub-industries, the challenges and promise of AI in healthcare domain, and the avenues to redefine healthcare in the coming years. OSP www.osplabs.com 1

4. Medical Diagnosis Challenges Lack of General Field Professionals Traditional Focus Mechanism Low Complications of Testing Minimal Clinical Interaction Financial Constraints Connectivity Process Algorithms EHR System Visual Analytics Equation Analysis Lab Data Model-based Logic User Interface Expert System Shell Symptom-Disease Knowledge Database Physiological Monitoring Real-time Pattern Detection Proactive Alerts AI Inference Engine Physician’s Notes Solutions Digital Imaging Cloud-based Platform Automated Diagnosis AI Lab Testing Image Analysis Predictive Analytics OSP www.osplabs.com 2

5. Use Cases ai in medical diagnosis helps to detect rare diseases clinical decision making can be enhanced with ai in medical diagnosis solutions ai in medical diagnosis can help to detect skin cancer ai in medical diagnosis has the potential to screen for tumors Benefits Tissue Phonemics toward Prevention Rare Object Identification Long Distance Association OSP www.osplabs.com 3

6. Medical Billing Challenges Complex Procedures Higher Workforce Requirement Unprecedented Workload Tedious Rectification High Cost Implications Inaccurate Coding Process EHR Encoder & CAC Processing ICD 9/ICD 10 CODES Handwritten Notes Coding & Billling Details Sent to Client Billing System Coder Input & QA Review Labs Orders/Results Other Documents Solutions Custom Billing Modules Advanced Reporting Billing CRM Management Payment Processing Claim Review System Clinical Documentation OSP www.osplabs.com 4

7. Use Cases ai can simplify medical billing with computer assisted coding (cac) advanced text analytics structures medical billing data ai in billing can easily predict potential claim denials ai can curb healthcare frauds with accurate analytics Benefits Computer Assisted Coding Data Anomaly Detection AI-based Workflow Optimization OSP www.osplabs.com 5

8. Pharma Challenges Shortage of Pharmacists Growing Demand for Prescriptions Affordable Healthcare Act Demands Increasing Operating Costs Lower Higher Patient Expectation Reimbursements Process Site Registry Deep Learning Target ID Engine Ethicacy Scores EMR EHR Adverse Effects Diseases Targeted Molecules Tissue-specific Effects Hypothesis Generation Drug Validation Claims Bioavailability Drug & Disease Database Synthetic Scalability Deep Learning Small Molecules Generation Engine Clinical Trials Leads Patent Solutions Automated Dispensing Holistic Caregiving Strategies Real-time Data Capturing Predictive Analysis Solutions Intelligent Analysis Algorithms Medical Augmentation OSP www.osplabs.com 6

9. Use Cases ai in pharma helps in risk-based monitoring (rbm) ai in pharma can help in drug target identification and validation phenotypic drug discovery is made possible with ai in pharma ai in pharma can help for polypharmacology discovery Benefits AI-based Pharma Drug Discovery Predictive Treatment Solution Neural Network Solutions for Pharmaceutical Processes OSP www.osplabs.com 7

10. Medical Imaging Challenges Disorganized Data Increasing Backlogs Reduced Profits and Reimbursements Exclusive Work Profile Rise in Competition Increased Patient Demands Process Feature Extraction Feature Selection Biomarker Identification Feature Classification Data & Code Statistics & Protocols Clinical Images Result Pre-Processing Feature Map Extraction Hyper Parameter Optimization Biomarker Validation Genomic Data Solutions AI Software Algorithms Real-time Medical Imaging Image Analysis Predictive Analysis Solutions Intelligent Algorithms for Image Analysis Data Mining Techniques OSP www.osplabs.com 8

11. Use Cases ai in medical imaging help to detect bone fractures ai in medical imaging identify cardiovascular abnormalities ai in medical imaging aid in the diagnosis of neurological diseases ai in medical imaging has the potential to screen for tumors Benefits Intelligent Imaging Analytics Cloud-based Whole Slide Imaging Platform AI-based Lung Nodule Detection OSP www.osplabs.com 9

12. Internet of thing(IoT) Challenges Higher Costs Manual Processes Unstructured Data Low Quality Services Low Operational Efficiency Weak Risk Analysis Process Data Preparation Web Data Source Data Catalogue Embedded Analysis Event Hub Mobile Apps SQL Data Warehouse Data Visualization Data Management Machine Learning Model Sensors Bots Solutions Easy to Integrate Sensors Device Management IoT Platforms Edge Processing Data Management Network Management and Support OSP www.osplabs.com 10

13. Use Cases ai iot solutions revolutionize medical imaging ai with iot can transform care homes with home automation ai in iot can redefine the sports biomechanics artificial intelligence can enhance fitness tracking devices Benefits Predictive Analytics Autonomous Intelligence Data Monitoring OSP www.osplabs.com 11

14. Pathology Challenges Lab Testing Outsourced Lack of Labeled Data Complicated Testing Process Low Clinical Interaction Financial Constraints Conventional Procedures Process Area Morphology Structure Generic Sub-type Identification Texture Feature Detection Whole Slide Image Database Tissue Patch-based Database CNN-based Feature Extraction Intensity Classification Feature Machine Learning Classifiers Result Output Parts Counting Segmentation Solutions Process Automation Image Analysis Predictive Analytics Rare Object Identification Morphology-based Segmentation Digital Whole Slide Imaging (WSI) OSP www.osplabs.com 12

15. Use Cases tissue phenomics made possible with ai in pathology ai in pathology can help in whole slide imaging ai helps to enhance diabetes retinopathy detection ai-driven digital pathology can help detect breast cancers Benefits Computer-assisted Diagnosis Tissue Analysis Tumor Detection OSP www.osplabs.com 13

16. Radiology Challenges Unstructured Data Appointment Backlogs Declining Reimbursements Lack of Clinical Involvement Increased Competition Higher Patient Expectation Process Automated Acquisition Diagnostic Inference Segmentation Dose Reduction Detection Medical Appointment Post Processing Registration Scan time Reduction Reporting Patient Record Result Decision Making Communication Quantification Acquisition Solutions Data Mining Image Processing Image Analysis Deep Learning Platforms Image Texture Analysis Algorithms Data Augmentation OSP www.osplabs.com 14

17. Use Cases ai can detect possibility of breast cancer from a mammogram ai can find abnormalities in chest x-rays machine learning algorithms can identify and grade ultrasound images ai can solve challenges of scoliosis imaging Benefits Automated Diagnostic Imaging Intelligent Cardiovascular Imaging AI-based Lung Nodule Detection OSP www.osplabs.com 15

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