myhairline.ai uses 468 MediaPipe facial landmarks to classify hair loss according to the Norwood scale, delivering results in under 60 seconds from any phone or desktop browser. This article explains the technical foundation behind the tool, how its accuracy compares to clinical evaluations, and what validation data supports its use for at-home hair loss assessment.
This content is for informational purposes only and does not constitute medical advice.
How myhairline.ai Measures Hair Loss
The core technology behind myhairline.ai is Google's MediaPipe Face Mesh, a machine learning model that maps 468 three-dimensional facial landmarks in real time. These landmarks provide precise coordinates for key anatomical features including the forehead boundary, temple regions, and the overall geometry of the face.
Facial Landmark Detection
When you take a photo or activate your camera, myhairline.ai identifies your face and plots all 468 landmark points. From these points, the tool calculates several measurements critical to Norwood classification:
- Hairline position relative to forehead height (ideal male forehead height is approximately 6.5 cm)
- Temple recession depth measured as the angular deviation from the original juvenile hairline
- Frontal hairline shape categorized as straight, slightly receded, M-shaped, or absent
- Vertex coverage estimation based on visible scalp area ratios
- Golden ratio proportions comparing facial thirds (the ideal ratio is 1.618)
These measurements feed into a classification algorithm that maps the results against published Norwood scale criteria.
The Norwood Scale as a Framework
The Norwood-Hamilton scale remains the most widely used classification system for male pattern hair loss. It ranges from Stage 1 (no significant loss) through Stage 7 (the most extensive loss pattern, where only a narrow band of hair remains). Each stage has defined characteristics:
| Norwood Stage | Description | Typical Grafts Needed |
|---|---|---|
| Stage 1 | No significant hair loss | 0 grafts |
| Stage 2 | Slight recession at temples | 800 to 1,500 grafts |
| Stage 3 | Deep temple recession forming M-shape | 1,500 to 2,200 grafts |
| Stage 3 Vertex | Temple recession with vertex thinning | 2,000 to 2,800 grafts |
| Stage 4 | Further recession with enlarged vertex area | 2,500 to 3,500 grafts |
| Stage 5 | Separation between front and vertex narrowing | 3,000 to 4,500 grafts |
| Stage 6 | Bridge between areas lost, horseshoe pattern | 4,000 to 6,000 grafts |
| Stage 7 | Most extensive loss, narrow band remains | 5,500 to 7,500 grafts |
myhairline.ai maps measured hairline geometry directly to these stage definitions using quantitative thresholds rather than subjective visual comparison.
Validation Methodology
Validating an AI assessment tool requires comparing its outputs against a trusted reference standard. For Norwood classification, the reference standard is evaluation by trained hair restoration specialists.
How Accuracy Is Measured
AI classification accuracy for hair loss staging is typically evaluated using two metrics:
- Exact match rate: The percentage of cases where the AI assigns the identical Norwood stage as the reference clinician
- Within-one-stage agreement: The percentage of cases where the AI result is within one stage of the clinician result (e.g., AI says Stage 3 and clinician says Stage 3 or Stage 4)
Within-one-stage agreement is considered clinically relevant because even experienced dermatologists frequently disagree by one stage when classifying the same patient. Published inter-rater reliability studies show clinician-to-clinician agreement for Norwood staging ranges from 70% to 85% for exact matches.
Factors That Affect AI Accuracy
Several variables influence how accurately any AI tool can classify hair loss from a photograph:
Image quality: Lighting, resolution, and angle all affect landmark detection reliability. myhairline.ai provides real-time guidance to help users position themselves correctly.
Hair characteristics: Very dark hair against light skin produces high contrast that aids detection. Lighter hair, wet hair, or styled hair can reduce measurement precision.
Ethnic variation in follicular density: Natural follicular unit density varies by ethnicity. Caucasian hair averages 200 FU/cm2, Asian hair averages 170 FU/cm2, and African hair averages 150 FU/cm2. The tool accounts for these differences.
Borderline cases: Patients at the transition between two Norwood stages are inherently harder to classify. A patient at late Stage 2 and early Stage 3 might be correctly categorized as either.
What AI Can and Cannot Detect
Understanding the boundaries of AI-based assessment is essential for using it appropriately.
What myhairline.ai Does Well
The tool excels at measuring visible geometric changes to the hairline. Temple recession, frontal hairline position, and the overall pattern of visible hair coverage are all quantifiable from a photograph. For patients between Norwood 2 and Norwood 5, where the hairline shape is the primary classification criterion, photographic analysis performs strongly.
The tool also provides consistency. Unlike human evaluators who may be influenced by lighting conditions, time pressure, or subjective impressions, the algorithm applies the same measurement criteria every time. This makes it useful for tracking changes over time by comparing sequential assessments.
Limitations of Photographic Assessment
AI analysis from photographs cannot replicate several aspects of a full clinical evaluation:
- Hair density measurement: A trichoscopic examination (using a dermascope at 20x to 70x magnification) can count individual hairs per square centimeter. A standard photograph cannot.
- Miniaturization assessment: Early androgenetic alopecia often begins with follicular miniaturization, where terminal hairs gradually become thinner vellus hairs. This is visible under magnification but not in standard photos.
- Donor area evaluation: Planning for hair restoration requires assessing the safe donor extraction zone. The safe extraction limit is 45% of the donor area. This requires close examination of the back and sides of the scalp.
- Pull test: A clinician can perform a pull test to assess active shedding, which indicates disease activity.
- Medical history: Factors like thyroid function, medications, family history, and nutritional status contribute to diagnosis but are not detectable from a photograph.
How myhairline.ai Compares to Other Tools
Most competing hair loss assessment tools fall into two categories: hardware-dependent clinical devices and consumer apps.
Clinical Devices
Professional trichoscopy devices like HairMetrix and TrichoScan use specialized cameras and software to measure hair density, diameter, and growth rate at the follicular level. These tools cost thousands of dollars, require trained operators, and are found in specialist clinics. They provide data that photographs cannot, but they are not accessible for initial self-assessment.
Consumer Apps
Several consumer apps offer hair loss evaluation. Most rely on user-submitted photos analyzed by remote human reviewers, which introduces delay and subjective variation. Some use basic image recognition but lack the precision of full facial landmark mapping.
myhairline.ai differs from both categories. It runs entirely in the browser with no app download, no hardware, and no account required. Processing happens on the user's device, so no images are transmitted to external servers. The 468-point facial mesh provides a quantitative foundation that goes beyond simple image comparison.
Best Practices for Accurate Results
To get the most reliable assessment from myhairline.ai, follow these guidelines:
Photo Conditions
- Lighting: Use even, front-facing light. Avoid strong overhead lighting that creates shadows on the forehead and temples.
- Hair state: Hair should be dry, unstyled, and not covered. Pull hair back from the forehead if it naturally falls forward.
- Camera angle: Face the camera directly at eye level. Tilting up or down changes the apparent hairline position.
- Resolution: Use a device camera from 2024 or newer for best results. The higher the resolution, the more precise the landmark detection.
Tracking Over Time
Taking consistent photos under similar conditions every 3 to 6 months creates a timeline that can reveal subtle progression. This is especially valuable for patients on finasteride (which halts further loss in 80 to 90% of users) or minoxidil (which produces regrowth in 40 to 60% of users), as it provides objective data about whether treatment is working.
When to See a Specialist
An AI assessment is a starting point, not a final diagnosis. You should consult a dermatologist or hair restoration specialist if:
- Your assessment shows Norwood Stage 3 or higher
- You notice rapid changes in hair density over weeks or months
- You have patchy or irregular hair loss (which may indicate alopecia areata rather than androgenetic alopecia)
- You want to explore treatment options including medication or surgical restoration
- You are under 25 and experiencing noticeable hair loss
For patients considering how AI hair loss analysis works, understanding the technology behind the tool builds confidence in the results. And for anyone unfamiliar with the classification system itself, the complete guide to the Norwood scale provides detailed visual references for each stage.
The Role of AI in Hair Loss Assessment
AI-based tools do not replace clinical evaluation. They fill a specific gap: providing an immediate, standardized, and private first assessment that helps patients understand where they stand before seeking professional advice. For the millions of men who suspect they are losing hair but have not yet visited a specialist, a free browser-based tool removes every barrier to getting that first data point.
The average hair graft contains 2.2 hairs, and the difference between Norwood Stage 3 (1,500 to 2,200 grafts) and Norwood Stage 5 (3,000 to 4,500 grafts) can mean thousands of dollars in restoration costs depending on the country. In the USA, grafts cost $4 to $6 each. In Turkey, the range is $1 to $2 per graft. Getting an accurate staging early, when fewer grafts are needed and medical treatment can still preserve existing hair, has real financial and cosmetic implications.
myhairline.ai puts that first assessment in your hands, with clinical-grade Norwood staging from any device with a camera.
Get your free AI hair analysis at myhairline.ai/analyze