AI in Healthcare Applications Training Course

Module 1: Foundations of AI in the Healthcare Ecosystem

• Understanding the shift from traditional evidence-based medicine to data-driven AI
• Distinguishing between descriptive, predictive, and prescriptive analytics in health
• Overview of the "Medical Data Deluge": Genomics, imaging, and wearable sensor data
• Exploring the role of AI in administrative efficiency and revenue cycle management
• Identifying the unique challenges of healthcare data: Sparsity, noise, and bias
• Practical session: Mapping a standard hospital workflow to identify potential AI intervention points

Module 2: Medical Imaging and Computer Vision

• Introduction to Convolutional Neural Networks (CNNs) for medical image analysis
• Processing DICOM files: Fundamentals of MRI, CT, and X-ray digital data
• Automated segmentation of tumors and anatomical structures in 3D imagery
• AI-assisted radiology: Improving sensitivity and reducing radiologist fatigue
• Challenges in medical vision: Small datasets, class imbalance, and labeling noise
• Practical session: Training a basic classifier to detect pneumonia in chest X-ray images

Module 3: Natural Language Processing for Electronic Health Records (EHR)

• Extracting clinical insights from unstructured physician notes and lab reports
• Named Entity Recognition (NER) for medical terms, medications, and dosages
• Converting unstructured EHR data into structured formats for downstream analytics
• Automated clinical coding and its impact on billing and health record accuracy
• Understanding medical sentiment and behavioral patterns through patient dialogue
• Practical session: Building an information extraction tool to identify drug-drug interactions from clinical text

Module 4: Predictive Analytics for Patient Outcomes

• Developing risk stratification models for chronic diseases like diabetes or heart failure
• Predicting hospital readmission rates and identifying high-risk patient cohorts
• AI-driven sepsis detection: Early warning systems in the Intensive Care Unit (ICU)
• Survival analysis: Using machine learning to predict time-to-event outcomes
• Interpreting black-box models: Why explainability is critical for physician trust
• Practical session: Implementing a random forest model to predict patient 30-day readmission risk

Module 5: AI in Drug Discovery and Genomics

• Accelerating the drug development lifecycle using molecular property prediction
• Understanding AI's role in protein folding and targeted therapy development
• Genomic data analysis: Identifying disease markers and personalized treatment paths
• Virtual screening and the simulation of clinical trials using digital twins
• The impact of AI on reducing the "valley of death" in pharmaceutical R&D
• Practical session: Exploring a genomic dataset to identify correlations between mutations and drug response

Module 6: Clinical Decision Support Systems (CDSS)

• Integrating AI models into the physician’s daily digital workspace
• Designing "Human-in-the-loop" systems that augment rather than replace clinicians
• Real-time monitoring and alert systems: Balancing sensitivity and "alert fatigue"
• Personalized treatment recommendations based on multi-modal patient data
• Evaluating the impact of CDSS on clinical workflow and patient safety
• Practical session: Designing a prototype interface for a real-time AI diagnostic assistant

Module 7: Healthcare Data Privacy, Security, and Ethics

• Navigating HIPAA, GDPR, and local health data regulations in the age of AI
• De-identification and anonymization techniques for medical datasets
• Identifying and mitigating algorithmic bias to ensure health equity for all populations
• Cybersecurity in health: Protecting AI systems and patient data from adversarial attacks
• Theoretical frameworks for the ethical use of autonomous systems in life-and-death decisions
• Practical session: Performing a privacy impact assessment and bias audit on a sample clinical model

Module 8: AI for Population Health and Epidemiology

• Using machine learning to predict and track the spread of infectious diseases
• Geospatial analysis for identifying social determinants of health and care gaps
• AI in telemedicine: Remote patient monitoring and proactive intervention strategies
• Analyzing large-scale public health data for resource allocation and planning
• Wearable technology integration: Transforming real-world data into clinical insights
• Practical session: Building a dashboard to visualize and predict local disease outbreaks

Module 9: Regulatory Frameworks and AI Model Validation

• Understanding the FDA/EMA pathways for "Software as a Medical Device" (SaMD)
• Clinical validation strategies: Sensitivity, specificity, and Area Under the Curve (AUC)
• The importance of "Prospective" vs. "Retrospective" studies in medical AI
• Post-market surveillance: Monitoring model performance and drift in the real world
• Documentation and transparency standards for regulatory submission
• Practical session: Drafting a validation plan for an AI diagnostic tool following regulatory guidelines

Module 10: Future Trends and Deploying AI in Clinical Practice

• Exploring the potential of Generative AI and LLMs in patient communication
• The rise of Edge AI: Bringing diagnostic power to point-of-care devices
• Strategy for organizational change management: Overcoming clinician resistance
• Financial modeling for AI adoption: Measuring Return on Investment (ROI) in health
• Roadmap for the next decade: Towards fully autonomous medical systems
• Practical session: Developing an AI adoption roadmap for a medium-sized healthcare facility

Requirements:

• Participants should be reasonably proficient in English.
• Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588