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Calmara, an app from HeHealth, claimed to detect signs of 10 or more sexually transmitted infections from penis photographs, with accuracy of up to 94.4%. But the evidence behind those claims did not match the marketing. After FTC scrutiny raised concerns about unconfirmed diagnoses, a small evaluation set, conflicted authorship, and a study covering only four conditions, HeHealth agreed to discontinue Calmara and delete submitted images.
That does not mean a formal trial proved that every result was wrong. It means Calmara was not a reliable substitute for clinical evaluation or validated STI testing—and its reassuring results could have been dangerous.
What Calmara was supposed to do
HeHealth launched Calmara in March 2024 as an AI-powered sexual-health app. Users could upload a photograph of a penis and receive an assessment of visible signs associated with conditions including syphilis, herpes, and HPV.
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That figure was a marketing claim, not an independently established clinical fact. “Up to 94.4% accuracy” does not necessarily mean 94.4% sensitivity or specificity for every infection, 94.4% accuracy among ordinary consumers, or reliable detection of infections that cause no visible symptoms.
HeHealth was the company; Calmara was the app that was discontinued. The available FTC documents do not establish that HeHealth itself shut down.
Why the app became a reality check for medical AI
Reporting summarized by Futurism described tests in which Calmara reportedly struggled to distinguish a penis from phallic inanimate objects. It reportedly classified a penis-shaped cake as clear and had difficulty with some textbook images showing STI symptoms.
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These were journalistic tests, not a formal clinical trial. Even so, they illustrated a fundamental problem: recognizing the general shape of an object is not the same as identifying disease. A system that cannot consistently identify what is in an image should not be trusted to interpret a medical condition in that image.
The memorable cake example is not the whole case. The more important questions concern how the model was trained, how its results were validated, and whether its advertising accurately described the evidence.
What the FTC questioned
In a July 11, 2024 closing letter, FTC staff described several problems with the support for Calmara’s health claims.
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Some image labels were not confirmed by diagnostic testing
Some images used to train or evaluate the model came from people who had not received microbiological, histological, or other diagnostic testing to establish whether an infection was actually present.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallThat matters because supervised machine learning depends on reliable labels. If an image is treated as showing an STI when the person was never diagnostically confirmed to have that infection, the model may learn visual correlations that do not correspond to disease. The same problem applies to supposedly negative images that were never properly tested.
The evaluation set was relatively small
The study acknowledged that the model was evaluated on a relatively small number of images. Small samples can produce unstable percentages and wide uncertainty, particularly for uncommon conditions.
Results from a limited dataset may also fail to generalize to ordinary consumer photographs with different lighting, focus, camera quality, skin tones, image compression, symptom stages, and patient populations. A model can perform well on images that resemble its development data while performing poorly in uncontrolled real-world use.
Most study authors had ties to HeHealth
According to the FTC letter, four of the study’s five authors worked for HeHealth or were paid consultants. That does not automatically invalidate the study, and it is not proof of fabrication or fraud. It does make independent replication and external validation especially important when the research is being used to support strong consumer health claims.
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The study and the advertising covered different numbers of conditions
The principal study described testing on four conditions, while Calmara’s marketing claimed detection of more than 10. Evidence for four conditions cannot automatically substantiate advertising for more than 10.
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This mismatch was one of the clearest problems in the case. A published paper, even if methodologically sound, supports only the population, conditions, methods, and performance actually studied. It does not provide a blanket license for broader claims.
Visible lesions are not the same as overall STI status
The FTC also questioned whether a model focused on visible marks or lesions could reliably identify asymptomatic infections. Many STIs may cause no noticeable symptoms, and visible changes may be absent at the time a photograph is taken.
A clear-looking image therefore cannot establish that someone is uninfected. It may only show that the photograph did not contain an obvious visual pattern the model recognized—and, in Calmara’s case, even that narrower capability was not adequately supported for the breadth of the advertising.
What happened to Calmara?
- March 2024: HeHealth launched Calmara, according to the FTC letter.
- April 2024: Los Angeles Times reporting exposed apparent weaknesses in the app’s image recognition.
- June 2024: FTC staff began scrutiny and issued a civil investigative demand, according to contemporaneous reporting.
- July 11, 2024: FTC staff issued the closing letter documenting its concerns.
- By July 15, 2024: HeHealth agreed to discontinue Calmara and delete data submitted through it, including uploaded images, according to reporting summarized by Futurism.
- July 18, 2024: The shutdown was widely reported.
Calmara should be treated as discontinued. The FTC’s case page and letter do not describe a court-ordered ban, criminal prosecution, civil penalty, or final adjudication that HeHealth committed fraud.
More precisely, FTC scrutiny exposed serious weaknesses in the support for Calmara’s claims, and HeHealth agreed to shut down the app and delete the data it had received. The FTC then closed its inquiry.
Why a photograph cannot replace an STI test
Some infections can produce visible signs, but photographs have fundamental limitations:
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- Some infections are asymptomatic or do not produce a distinctive lesion.
- Different infections—and noninfectious conditions—can look similar.
- Irritation, dermatitis, fungal infections, allergies, trauma, and normal anatomical variation may be mistaken for an STI-related condition.
- Lighting, focus, cropping, skin tone, camera quality, and compression can change what an image appears to show.
- A photograph cannot directly establish the presence of organisms, antibodies, viral material, or other laboratory markers.
- A negative visual result can create false reassurance and discourage testing or safer-sex precautions.
A useful medical-image system would need rigorous clinical validation against confirmed laboratory or clinical diagnoses. It would also need to publish performance by condition, symptom status, skin tone, age, image quality, and other relevant factors. Calmara’s evidence, as characterized by the FTC, did not support the certainty or scope of its consumer marketing.
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The privacy and consent problem
Accuracy was not the only concern. A service built around genital photographs creates unusually sensitive privacy and safety risks.
- A user might upload another person’s intimate photograph without that person’s consent.
- Users may not understand how long images are retained, who can review them, or whether they can be used to train models.
- A health-oriented image database is a valuable security target.
- A false positive could lead to stigma, harassment, relationship conflict, or unnecessary anxiety.
- A false negative could encourage unprotected sex or delay treatment.
These are privacy, consent, security, and consumer-safety risks—not findings that Calmara necessarily violated a particular privacy law. The applicable legal outcome would depend on the facts and jurisdiction.
As later context, the FTC says it began enforcing the notice-and-removal provisions of the TAKE IT DOWN Act on May 19, 2026. That development concerns qualifying nonconsensual intimate imagery and is not the legal basis for Calmara’s 2024 shutdown.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to evaluate a future AI medical-image app
“AI-powered” and “science-backed” are descriptions, not proof of clinical validity. Before trusting a health app, ask:
- What is the intended use? Is it education, triage, screening, diagnosis, or treatment guidance? Each requires different evidence.
- What was the reference standard? Were positive and negative cases confirmed with laboratory or clinical testing?
- Was the evaluation independent? Were the researchers employed or paid by the vendor, and has an outside group replicated the findings?
- Are the metrics complete? Look for sensitivity, specificity, positive and negative predictive value, confidence intervals, and results by condition—not just a single “accuracy” number.
- Does the advertising match the study? Four studied conditions do not support claims about 10 or more without additional evidence.
- Does the product have appropriate clinical validation or regulatory status? App-store availability and a published paper are not equivalent to clearance or validation for a diagnostic use.
- What happens to intimate images? Check retention, encryption, human review, model-training permissions, deletion controls, third-party sharing, and consent requirements.
What readers should do instead
Do not use an image-based AI result to decide whether sex is safe, whether testing is unnecessary, or whether a partner has an STI. If you have symptoms, a recent exposure, or uncertainty about your status, contact a clinician or sexual-health clinic and ask about appropriate testing.
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Options may include in-person services such as Planned Parenthood health centers, telehealth services such as Nurx where available, or laboratory-based services such as Everlywell’s at-home STI testing and STDCheck. Availability, panels, prices, clinical review, and follow-up vary. At-home testing may not cover every infection and may be inappropriate for urgent symptoms or lesions that require examination.
The safe principle is simple: use validated testing and professional medical advice, not a reassuring interpretation of an intimate photograph.
The broader lesson for AI health products
Calmara’s failure was not merely a funny image-classification story. It showed how quickly a narrow or uncertain research result can become a broad consumer promise.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsMedical AI claims need reliable diagnostic labels, appropriately sized and representative evaluations, independent validation, transparent metrics, and privacy protections proportionate to the sensitivity of the data. Most importantly, the product’s marketing must not outrun its evidence.
For Calmara, the evidence described by the FTC did not justify presenting an image classifier as an immediate answer about a person’s STI status. The app is gone, but that lesson applies to any future health product asking consumers to trust a confident number more than a properly conducted test.
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