Confirmed podcast hosts include Stacey Abrams ("Assembly Required With Stacey Abrams"), Chanel Nicole Scott ("Relationships Matter", "Crowned"), Marlo Hampton ("The Real Close Friends"), and Kim Zolciak (formerly hosted "House of Kim"). Others like Molly Hopkins and Mimi Faust have participated as guests on relevant podcasts.  

April

1. Stress Awareness – Body's response to demand.
   Mechanism: Triggers HPA axis → cortisol.
   55% of Americans stressed daily. Stress-related absences cost $300B/year. Chronic stress shrinks brain regions. Yoga reduces cortisol.
   
   

2. Autism – Neurodevelopmental disorder.
   Mechanism: Early brain overgrowth, synaptic dysfunction.
   1 in 36 US kids; 75M globally. Boys 4x more affected. Early diagnosis boosts outcomes.
   
   

3. Minority Health – Disparities by race/ethnicity.
   Mechanism: Socioeconomic gaps, systemic bias.
   Black adults 40% more likely to have hypertension. Latinx less likely to access care. Inequities cost $93B/year.
   
   

4. Parkinson’s – Progressive motor disorder.
   Mechanism: Dopamine neuron loss in substantia nigra.
   1M in US; 10M globally. 60K new US cases yearly. Exercise delays progression.
   
   

5. IBS – Chronic gut disorder.
   Mechanism: Brain-gut axis dysfunction, serotonin shifts.
   Affects 10–15% of US adults. Women 2x more affected. FODMAP diet effective in 75%.
   
   

6. Injury Prevention – Reducing harm risks.
   Mechanism: Environmental changes, protective behaviors.
   200K US deaths annually. Falls lead in seniors. Car seats cut child crash deaths 71%.
   
   

7. Joint Health – Mobility via joint preservation.
   Mechanism: Cartilage + synovial fluid protect joints.
   1 in 4 US adults have arthritis. Obesity worsens joint damage. Exercise reduces pain.
   
   

May

1. Mental Health – Emotional/psychological balance.
   Mechanism: Neurochemical + cognitive function.
   1 in 5 US adults affected. Suicide is 2nd leading teen cause. Therapy + meds help recovery.
   
   

2. Arthritis – Joint inflammation.
   Mechanism: Cartilage breakdown, immune response.
   58.5M in US. Osteoarthritis is most common type. Movement and weight control reduce symptoms.
   
   

3. Stroke – Blood flow to brain blocked.
   Mechanism: Clot or rupture impairs oxygen.
   795K US strokes yearly. Every 40 seconds, a stroke occurs. FAST action saves lives.
   
   

4. Osteoporosis – Low bone density.
   Mechanism: Bone resorption exceeds formation.
   10M Americans affected; 80% are women. 1 in 2 women over 50 will break a bone.
   
   

5. Women’s Health – Female-specific care.
   Mechanism: Hormonal + reproductive systems focus.
   Heart disease is top female killer. Only 20% recognize symptoms. Mammograms save thousands yearly.
   
   

6. Physical Fitness – Activity for health.
   Mechanism: Boosts metabolism, endorphins, muscle function.
   Only 23% meet exercise guidelines. Reduces heart disease risk by 35%. Also improves sleep.
   
   

7. Sports Injury Prevention – Reduce athletic harm.
   Mechanism: Conditioning, warmups, technique.
   Injuries in 3.5M US kids/year. Warm-ups cut risk 30%. ACL tears common in female athletes.
   
   

8. Fibromyalgia Awareness – Chronic pain/fatigue condition.
   Mechanism: CNS amplifies pain signals.
   4M US adults affected. 80–90% are women. Sleep + stress control improves quality of life.
   
   

June

1. Brain Awareness – Focus on cognitive health.
   Mechanism: Neurons transmit signals; vulnerable to damage.
   Alzheimer’s affects 6.9M US. Brain games, sleep, and diet aid function. Neuroplasticity continues lifelong.
   
   

2. Men’s Health – Male-specific health concerns.
   Mechanism: Hormonal, behavioral factors.
   Men die 5 years earlier than women. Less likely to visit doctors. Testicular cancer peaks at age 30.
   
   

3. PTSD – Trauma-related anxiety disorder.
   Mechanism: Hyperactive amygdala, cortisol dysregulation.
   13M US cases/year. 7% will experience it. Veterans at higher risk. EMDR is effective therapy.
   
   

4. Migraine – Recurring head pain.
   Mechanism: Neurovascular inflammation, serotonin shifts.
   39M US; 1B worldwide. Women 3x more affected. Triggers include light, food, stress.
   
   

5. Alzheimer’s & Dementia – Memory/cognition decline.
   Mechanism: Beta-amyloid plaques, tau tangles.
   6.9M US cases. 1 in 3 seniors dies with dementia. No cure; lifestyle delays symptoms.
   
   

6. National Safety Month – Injury awareness & prevention.
   Mechanism: Training + hazard reduction.
   Injuries = 4th US death cause. PPE and safety drills reduce risk. 2.6M job injuries/year.
   
   

7. Spine Health – Back care & function.
   Mechanism: Discs, vertebrae protect nerves.
   80% experience back pain. Poor posture + lifting technique are key factors. Core strength helps.
   
   

8. Work Safety Month – Jobsite injury prevention.
   Mechanism: Ergonomics, protocols, training.
   2.6M injuries in 2021. Falls top cause. Safety programs cut accidents by 40%.
   
   

July

1. Healthy Vision – Eye function & protection.
   Mechanism: Retina captures light, brain interprets.
   12M US have vision loss. 80% preventable. Diabetes is top cause of blindness.
   
   

2. UV Safety – Skin/eye sun protection.
   Mechanism: UV rays damage DNA in cells.
   1 in 5 Americans get skin cancer. 90% from sun exposure. SPF 30+ blocks 97% UVB.
   
   

3. Minority Mental Health – Equitable care for BIPOC.
   Mechanism: Cultural stigma + access barriers.
   Black adults 50% less likely to receive care. Language gaps worsen outcomes. Culturally sensitive therapy works better.
   
   

4. Chronic Disease Management – Long-term illness control.
   Mechanism: Ongoing care + lifestyle shifts.
   6 in 10 US adults have chronic disease. 4 in 10 have two or more. Prevention saves billions.
   
   

5. Scoliosis Awareness – Spinal curve disorder.
   Mechanism: Unknown, likely genetic + growth factors.
   6–9M in US. Most cases mild. Common in teen girls. Bracing helps avoid surgery.
   
   

[Office: 7-5p Mon-Thu | Outreach 6-8pm Mon-Wed] 

Daily Routine

#1 6:30 AM – Hydration & Meta Boost - 20 oz lemon water or apple cider vinegar water to kickstart digestion.

#2 7 AM – Breakfast - Egg white & kale omelet with grilled chicken breast and dairy-free cheese.

• Alternative: Smoked salmon & avocado on almond flour toast.

#3 7:30 AM – Workout (10-20 min) - Planks, Brisk walk, bodyweight training, or resistance band exercises.

#4 10 AM – Snack - Egg white, Hard-boiled eggs & almonds or Greek yogurt (dairy-free) with b-berries, flaxseeds.

#5 12 PM – Lunch  (Protein Smoothie or Salad) - Apple, avocado, almond milk smoothie w/ protein, fruit, vitamins

• Alternative: Grilled chicken w/ spinach/kale & olive oil dressing or vegetarian (wrap, salad, etc) 

#6 3 PM – Movement (10-20 min) - Quick HIIT session or stretching/yoga for recovery.

#7 4 PM – Protein Snack - Tuna salad (olive oil, mustard, celery), Chicken, tomatoes w/ hummus.

#8 7 PM – Dinner - Grilled salmon / Chicken, roasted Brussels sprouts, & mixed greens salad.

• Alternative: Lemon herb chicken breast with zucchini noodles.

#9 8 PM – Evening Wind-Down - Herbal tea (chamomile or peppermint) & deep breathing exercises.

#10 10 PM – Sleep Routine - 7-9 hours of quality sleep in a cool, dark, screen-free room.

• LinkedIn

• Days: Mo, Tu, We, Th | 7a, 12p, 5p  [ Fr-Su  7a | Reposts ]  15x

• AM: Leadership/Motivational.  Early PM: Insights/Polls. PM: Case Studies/Stories/Highlights

Orientation Module | WELCOME TO YOUR ONLINE CAMPUS

You’ll be welcomed to the course and begin connecting with fellow participants, while exploring the navigation and tools of your Online Campus. Be alerted to key milestones in the learning path, and review how your results will be calculated and distributed.

You’ll be required to complete your participant profile and submit a digital copy of your passport/identity document.

Module 1 AI AND MACHINE LEARNING — APPLICATIONS AND FOUNDATIONS

Become familiar with supervised machine learning and the types of problems it may be applied to.

• Identify the basics of machine learning, neural networks, and deep learning

• Indicate the ways in which AI may be applied to health care

• Review misconceptions and challenges relating to AI

• Outline important questions to gauge the suitability of AI in health care

Module 2 USING AI FOR DISEASE DIAGNOSIS AND PATIENT MONITORING

Examine real-world applications of AI for diagnosis and patient monitoring.

• Articulate the burdens on health care, which may be addressed using AI diagnostic and monitoring techniques

• Analyze the challenges associated with implementing AI diagnostic and monitoring techniques

• Recommend questions to determine the suitability of AI in different health care contexts

Module 3 NATURAL LANGUAGE PROCESSING AND DATA ANALYTICS IN HEALTH CARE

Use AI to extract value-adding outcomes from medical literature and pathology reports.

• Relate how natural language processing (NLP) can be used to explore and classify medical data

• Deduce how data analysis using AI techniques can be used to improve health care outcomes

• Investigate potential challenges to the adoption of AI-driven data management techniques

• Analyze the suitability of standard NLP models and customized NLP models

• Recommend questions to determine the suitability of AI in different health care contexts

Module 4 INTERPRETABILITY IN MACHINE LEARNING — BENEFITS AND CHALLENGES

Appreciate the importance and benefits of interpretable algorithms.

• Review the concept of interpretability and why it is important for decision making in health care

• Articulate the challenges to developing interpretability in AI models

• Analyze important design traits and considerations necessary for AI to be implemented in health care

• Recommend questions to determine the suitability of AI in different health care contexts

Module 5 PATIENT RISK STRATIFICATION AND AUGMENTING CLINICAL WORKFLOWS

Discover how AI can be applied to health care interventions and patient care.

• Outline how machine learning techniques can be applied to clinical care and administration

• Determine the practical considerations of using machine learning for patient risk stratification

• Investigate cases where machine learning can be used to augment clinical workflows

• Analyze different considerations in using AI for risk stratification and health care management

• Assess the potential benefits of machine learning in hospital process augmentation

• Recommend questions to determine the suitability of AI in different health care contexts

Module 6 TAKING AN INTEGRATED APPROACH TO HOSPITAL MANAGEMENT AND OPTIMIZATION

Investigate a holistic approach to optimizing health care processes.

• Relate the ways that AI can aid in optimizing hospital processes

• Investigate how AI predictive power can be applied to inpatient needs and processes

• Analyze challenges to implementing AI-enabled optimization processes in hospitals

• Assess the role of AI in creating holistic hospital optimization

• Evaluate the viability of using AI in a given health care context

 Orientation Module | WELCOME TO YOUR ONLINE CAMPUS

You’ll be welcomed to the course and begin connecting with fellow participants, while exploring the navigation and tools of your Online Campus. Be alerted to key milestones in the learning path, and review how your results will be calculated and distributed.

You’ll be required to complete your participant profile and submit a digital copy of your passport/identity document.

Module 1 AI AND MACHINE LEARNING — APPLICATIONS AND FOUNDATIONS

Become familiar with supervised machine learning and the types of problems it may be applied to.

• Identify the basics of machine learning, neural networks, and deep learning

• Indicate the ways in which AI may be applied to health care

• Review misconceptions and challenges relating to AI

• Outline important questions to gauge the suitability of AI in health care

Module 2 USING AI FOR DISEASE DIAGNOSIS AND PATIENT MONITORING

Examine real-world applications of AI for diagnosis and patient monitoring.

• Articulate the burdens on health care, which may be addressed using AI diagnostic and monitoring techniques

• Analyze the challenges associated with implementing AI diagnostic and monitoring techniques

• Recommend questions to determine the suitability of AI in different health care contexts

Module 3 NATURAL LANGUAGE PROCESSING AND DATA ANALYTICS IN HEALTH CARE

Use AI to extract value-adding outcomes from medical literature and pathology reports.

• Relate how natural language processing (NLP) can be used to explore and classify medical data

• Deduce how data analysis using AI techniques can be used to improve health care outcomes

• Investigate potential challenges to the adoption of AI-driven data management techniques

• Analyze the suitability of standard NLP models and customized NLP models

• Recommend questions to determine the suitability of AI in different health care contexts

Module 4 INTERPRETABILITY IN MACHINE LEARNING — BENEFITS AND CHALLENGES

Appreciate the importance and benefits of interpretable algorithms.

• Review the concept of interpretability and why it is important for decision making in health care

• Articulate the challenges to developing interpretability in AI models

• Analyze important design traits and considerations necessary for AI to be implemented in health care

• Recommend questions to determine the suitability of AI in different health care contexts

Module 5 PATIENT RISK STRATIFICATION AND AUGMENTING CLINICAL WORKFLOWS

Discover how AI can be applied to health care interventions and patient care.

• Outline how machine learning techniques can be applied to clinical care and administration

• Determine the practical considerations of using machine learning for patient risk stratification

• Investigate cases where machine learning can be used to augment clinical workflows

• Analyze different considerations in using AI for risk stratification and health care management

• Assess the potential benefits of machine learning in hospital process augmentation

• Recommend questions to determine the suitability of AI in different health care contexts

Module 6 TAKING AN INTEGRATED APPROACH TO HOSPITAL MANAGEMENT AND OPTIMIZATION

Investigate a holistic approach to optimizing health care processes.

• Relate the ways that AI can aid in optimizing hospital processes

• Investigate how AI predictive power can be applied to inpatient needs and processes

• Analyze challenges to implementing AI-enabled optimization processes in hospitals

• Assess the role of AI in creating holistic hospital optimization

• Evaluate the viability of using AI in a given health care context