Background:　and　Purpose:　Thermal　radiation　plays　a　pivotal　role　in　addressing　recognition　limitations　encountered　by　traditional　Chinese　medicine＇s　tongue　diagnosis.　Modern　thermal　radiation　diagnostic　instruments　offer　enhanced　objectivity,　and　in　this　study,　we　strive　to　further　improve　the　diagnostic　process　through　the　integration　of　Human-Computer　Interaction　(HCI)　principles.　Our　objective　is　to　introduce　the　thermal　radiation　DenseNet　ensemble　model,　synergizing　the　strengths　of　Convolutional　Neural　Networks　(CNNs)　and　HCI　principles　to　advance　tongue　image　recognition　in　healthcare.　This　approach　aims　to　enhance　classification　accuracy,　even　when　faced　with　limited　training　data.　Methodology:　Transfer　learning,　utilizing　fine-tuned　CNNs　and　DenseNet,　is　employed　for　precise　classification,　with　a　specific　focus　on　distinguishing　tooth-marked　tongues.　A　portable　hand-held　thermal　radiation　diagnostic　instrument,　seamlessly　integrated　with　HCI,　is　developed　for　both　clinical　use　and　research.　Experimental　results:　Meticulously　curated　datasets,　formed　through　the　annotation　of　thermal　radiation　images,　confirm　the　superior　performance　of　the　DenseNet　architecture　in　tooth　mark　and　tongue　feature　recognition.　The　proposed　tooth　mark　tongue　recognition　model　exhibits　a　significant　accuracy　improvement　of　approximately　25%　compared　to　similar　tasks　in　existing　studies.　Additionally,　an　AI　health　detector　tailored　for　Traditional　Chinese　Medicine　(TCM)　thermal　radiation　image　recognition　is　introduced,　showcasing　the　seamless　integration　of　HCI　principles　into　healthcare　applications.　This　innovative　tool　not　only　assesses　users＇　health　but　also　provides　personalized　health　recommendations,　illustrating　the　transformative　potential　of　combining　technology　and　healthcare.　Discussion　and　conclusion:　In　addressing　the　limitations　of　traditional　tongue　diagnosis,　thermal　radiation　emerges　as　a　key　factor　enhancing　objectivity　and　accuracy.　The　thermal　radiation　DenseNet　ensemble　model,　along　with　HCI　integration　through　the　portable　hand-held　device,　proves　effective　for　improved　TCM　thermal　radiation　image　identification　in　healthcare.　The　fusion　of　technology　and　HCI　principles　underscores　the　potential　to　elevate　health　assessments　and　offer　valuable　guidance　to　users.