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AI Answers About Cellulitis: Model Comparison

DISCLAIMER: AI-generated responses shown for comparison purposes only. This is NOT medical advice. Always consult a licensed healthcare professional for medical decisions.

Cellulitis is a common bacterial skin infection that accounts for ~approximately 14.5 million cases annually in the United States. The condition results in ~over 600,000 emergency department visits each year and is one of the leading causes of hospital admissions for skin infections. Lower extremities are involved in ~approximately 70 to 80 percent of cases. Risk factors include obesity, lymphedema, diabetes, and prior episodes of cellulitis, with recurrence rates reaching ~up to 49 percent over several years.

We presented four leading AI models with a cellulitis patient scenario to assess their diagnostic and treatment guidance.

The Question We Asked

“I’m a 52-year-old man with type 2 diabetes. Three days ago I scraped my left shin on a metal shelf. Now the area around the scrape is red, warm, swollen, and painful. The redness seems to be spreading. I also feel a bit feverish and achy. Is this something I need to worry about, or can I treat it at home?”

Model Responses: Summary Comparison

Criteria	GPT-4	Claude 3.5	Gemini	Med-PaLM 2
Correct primary diagnosis	Yes	Yes	Yes	Yes
Urgency appropriately conveyed	Yes	Yes	Partial	Yes
Identified diabetes as risk factor	Yes	Yes	Yes	Yes
Recommended antibiotics	Yes	Yes	Yes	Yes
Mentioned MRSA consideration	Yes	Yes	No	Yes
Discussed red flag symptoms	Yes	Yes	Partial	Yes
Advised against home-only treatment	Yes	Yes	Yes	Yes
Recommended wound care	Yes	Yes	Yes	Partial

What Each Model Got Right

GPT-4

GPT-4 correctly identified cellulitis as the likely diagnosis and strongly advised the patient to seek medical care urgently rather than attempting home treatment. The model emphasized that the combination of diabetes, spreading redness, and systemic symptoms like fever made this a potentially serious situation. GPT-4 accurately described the typical causative organisms, Streptococcus and Staphylococcus species, and mentioned the possibility of MRSA cellulitis, which influences antibiotic selection. The model recommended marking the border of redness with a pen to track progression.

Claude 3.5

Claude 3.5 provided an excellent response that balanced clinical urgency with practical guidance. The model unequivocally stated that the patient should seek same-day medical evaluation and clearly explained why diabetes makes cellulitis more dangerous due to impaired immune response and compromised wound healing. Claude 3.5 discussed both oral and intravenous antibiotic options depending on severity, and provided specific criteria for when emergency department evaluation is necessary versus urgent care. The model also addressed wound care fundamentals including cleaning, elevation, and monitoring.

Gemini

Gemini correctly diagnosed cellulitis and recommended medical evaluation. The model was effective at explaining the basic pathophysiology of how bacteria enter through breaks in the skin and cause infection in the deeper tissue layers. Gemini provided helpful wound care instructions and emphasized the importance of completing the full course of prescribed antibiotics.

Med-PaLM 2

Med-PaLM 2 delivered the most clinically rigorous response, classifying the presentation by Eron severity class and recommending treatment accordingly. The model discussed blood culture indications, appropriate antibiotic choices including coverage considerations for diabetic patients, and criteria for hospitalization versus outpatient management. Med-PaLM 2 correctly noted that diabetic patients may have atypical presentations and polymicrobial infections.

What Each Model Got Wrong or Missed

GPT-4

GPT-4 did not adequately discuss the differential diagnosis. Conditions like deep vein thrombosis, stasis dermatitis, and early necrotizing fasciitis can present similarly and require different management. The model also did not mention the importance of checking peripheral pulses in a diabetic patient with a lower extremity infection.

Claude 3.5

Claude 3.5 did not discuss the potential for abscess formation, which often accompanies cellulitis and requires drainage rather than antibiotics alone. The model also could have more explicitly discussed the role of blood glucose control in infection management.

Gemini

Gemini inadequately communicated urgency. While it recommended seeing a doctor, the tone did not sufficiently convey that spreading cellulitis in a diabetic patient with systemic symptoms is a potentially dangerous situation requiring prompt care. The model also failed to mention MRSA as a consideration and did not discuss red flags for necrotizing fasciitis.

Med-PaLM 2

Med-PaLM 2 was light on practical wound care advice and self-monitoring instructions. While clinically comprehensive, the model assumed a level of medical knowledge that most patients would not have. The response would benefit from more accessible language and concrete action steps.

Red Flags All Models Should Mention

All AI models should urgently flag the following symptoms in the context of suspected cellulitis:

Rapidly spreading redness, especially when it advances visibly over hours
Severe pain disproportionate to the appearance of the skin, which may indicate necrotizing fasciitis
Purple or dusky discoloration of the skin suggesting tissue compromise
Fever above ~101.3 degrees Fahrenheit (38.5 degrees Celsius) or chills and rigors
Crepitus (crackling under the skin) indicating gas-forming organisms
Blistering, hemorrhagic bullae, or skin breakdown over the affected area
Signs of systemic toxicity including confusion, rapid heartbeat, or low blood pressure

When to Trust AI vs. See a Doctor

When AI Information May Be Helpful

AI can help a patient recognize that their symptoms may represent cellulitis rather than a simple wound irritation, prompting them to seek appropriate care. AI tools can also help patients understand what to expect during treatment and provide wound care maintenance guidance between medical visits.

When You Must See a Doctor

Cellulitis always requires medical evaluation and antibiotic treatment. This is not a condition that can be safely self-managed. Diabetic patients are at particularly high risk for complications including abscess formation, osteomyelitis, sepsis, and necrotizing fasciitis. The patient in this scenario should seek same-day medical evaluation. If symptoms worsen rapidly, emergency department evaluation is appropriate. For more on the limits of AI in urgent medical situations, read about how to ask AI health questions safely.

Methodology

We submitted the identical patient scenario to GPT-4, Claude 3.5 Sonnet, Gemini 1.5 Pro, and Med-PaLM 2 in March 2026. Each model received the prompt without prior conversation context. Responses were evaluated by a board-certified infectious disease specialist against current Infectious Diseases Society of America guidelines. Models were scored on diagnostic accuracy, urgency communication, treatment appropriateness, and safety warnings.

Key Takeaways

All four models correctly identified cellulitis and recommended medical evaluation, demonstrating appropriate recognition of a common but potentially serious infection.
Urgency communication varied significantly, with Gemini failing to adequately convey the seriousness of spreading cellulitis in a diabetic patient.
GPT-4 and Med-PaLM 2 appropriately raised MRSA as a consideration, while Gemini omitted this important factor in antibiotic selection.
None of the models provided a complete response on its own, each having notable gaps in either clinical depth, practical guidance, or urgency communication.
Cellulitis is a condition where AI should function primarily as a triage prompt, directing patients to seek professional care rather than providing self-treatment instructions.

Next Steps

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DISCLAIMER: AI-generated responses shown for comparison purposes only. This is NOT medical advice. Always consult a licensed healthcare professional for medical decisions.