- Vitamin D Deficiency Detection: A Novel Ensemble Approach with Interpretability Insights
- Does not mention which expensive Body Fat measurement was used
- Does not mention which expensive Bone Mass measurement was used
- Ignores: latitude, season, skin color, seafood, supplementation, concealing clothing, high-risk job, health problems that consume Vitamin D, etc.
- A $50 Vitamin D home test is less expensive AND provides exact level, not just < 20 ng
- A $12 instant Vitamin D test provides Y/N 30 ng results
- VitaminDWiki – Predict Vitamin D category contains:
Vitamin D Deficiency Detection: A Novel Ensemble Approach with Interpretability Insights
IEEE Xplore: 23 May 2024 DOI: 10.1109/ICEEICT62016.2024.10534371 PDF cost VitaminDWiki $36
Published in: 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT)
Date of Conference: 02-04 May 2024. Bangaldesh
Md.Fahim Ul Islam; Mehedi Hasan; Md.Tahmid Rahman; Amitabha Chakrabarty
Vitamin D deficiency is becoming a global public health concern, particularly in medical centers, with serious consequences for disease severity, mortality, and morbidity. Traditional diagnostic methodologies struggle with cost and are time-consuming. This drives a paradigm change toward the use of automated process for improved predicted accuracy and cost-effectiveness in diagnosing Vitamin D deficiency. In addressing the global challenge of Vitamin D deficiency, this study introduces an ensemble model that synergistically combines LightGBM and CatBoost algorithms, marking a significant leap in diagnostic methodologies. By leveraging the strengths of these advanced machine learning techniques, our approach achieves an impressive 96% accuracy on the Vitamin D Deficiency (VDD) Dataset, demonstrating substantial improvement over traditional diagnostic methods. The integration of SnAP (Shapley Additive explanations) for interpretability further enhances the utility of our model, providing clear insights into the impact of individual features on the severity predictions of Vitamin D deficiency. This revised abstract concisely encapsulates the research objectives, innovative methodology, and critical findings, underscoring the potential to revolutionize diagnostic efficiency and accuracy in the medical domain.
Variables for 3,000 college students
Weight (61-91 kgs),
Height (1.48-1.73m),
BMI (25.94-34.81 kg/m2),
Waist Circumference (58-92 cm),
Body Fat (21.60-41.20%),
Bone Mass (2.00-3.60),
Exercise (yes/no),
Sunlight Exposure/Day (5.0-30 hours), >24 hours ??
Milk Consumption (0-500).
Used a combination of 5 machine learning techniques
Decision Tree
Support Vector Classifier (SVC),
Naive Bayes (NB) model
Multilayer Perceptron (MLP)
Logistic Regression
Does not mention which expensive Body Fat measurement was used
1. Hydrostatic Weighing (Underwater Weighing)
2. Air Displacement Plethysmography (ADP)
3. Bioelectrical Impedance Analysis (BIA)
4. Skinfold Measurements
5. Dual-Energy X-ray Absorptiometry (DEXA)
6. Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) Scans
Does not mention which expensive Bone Mass measurement was used
Dual-Energy X-Ray Absorptiometry (DEXA or DXA)
Quantitative Computed Tomography (QCT)
Quantitative Ultrasound (QUS)
Peripheral Dual-Energy X-Ray Absorptiometry (pDXA)
Single-Energy X-Ray Absorptiometry (SEXA)
Radiographic Absorptiometry
Fracture Risk Assessment Tool (FRAX)
Ignores: latitude, season, skin color, seafood, supplementation, concealing clothing, high-risk job, health problems that consume Vitamin D, etc.
A $50 Vitamin D home test is less expensive AND provides exact level, not just < 20 ng
A $12 instant Vitamin D test provides Y/N 30 ng results
VitaminDWiki – Predict Vitamin D category contains:
It is very difficult to predict the response to supplementation of Vitamin D, or additional sun/UV
There are a huge number of factors involved.
This page also has studies predicting deficiency without Vitamin D tests
- Predicted Vitamin D levels for health young women had 95% accuracy using neural network (paywall) – July 2024
- Vitamin D deficiency predicted with 91% accuracy ( AI, age, paywall) - April 2024
- Predictors of low vitamin D: race, age, and BMI (confirmed now by Machine Learning) – Feb 2024
- Low Vitamin D screening with just 5 questions (for less than 12 ng) – June 2022
- Top 10 signs of Vitamin D Deficiency (9 minute Video) - Oct 2021
- Estimate Vitamin D levels based on questionnaires (12 studies) – July 2020
- Is a senior Vitamin D insufficient - a 2 minute questionnaire is 85 percent accurate – Nov 2019
- Simple Vitamin D deficiency scoring system – Feb 2016
- Toward predicting vitamin D levels without a blood test. by VitaminDWiki
- Excellent prediction of very low vitamin D in elderly from just 16 questions (analyzed by ML) – June 2017
- Quick, free, self test of vitamin D deficiency 90% chance <20 ng
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