Name: WYCTOR FOGOS DA ROCHA
Publication date: 10/07/2026
Examining board:
Name |
Role |
|---|---|
| JOÃO PAULO PAPA | Examinador Externo |
| LUIS ANTONIO DE SOUZA JUNIOR | Presidente |
| THIAGO OLIVEIRA DOS SANTOS | Examinador Interno |
Summary: Automatic skin lesion classication has advanced substantially with deep learning in recent
years, yet many systems still rely predominantly on image information while making
limited use of complementary clinical data. This restricts their ability to more realistically
reproduce the dermatological diagnostic process, which naturally combines visual evidence
with patient context. In this scenario, multimodal strategies for skin lesion classication
were investigated, with emphasis on the integration of dermoscopic images and clinical
metadata.
The problem was addressed from four complementary perspectives: explicit modeling of
imagemetadata interaction through attention-based mechanisms; analysis of the inuence
of clinical attributes on the decision-making process; development of more stable and
controlled multimodal fusion strategies; and automatic search for competitive architectures under practical constraints. In addition, robustness to incomplete metadata was
explored through semantically richer textual representations as an alternative to traditional
categorical encodings.
The results indicate that carefully designed multimodal architectures can outperform
unimodal approaches and simple fusion strategies, particularly in terms of balanced
accuracy. They also show that the way metadata is incorporated directly affects model
stability, interpretability, and robustness, while residual and attention-based mechanisms
contribute to a more controlled fusion process. In parallel, architecture optimization
through search demonstrated potential to identify compact and competitive solutions.
Taken together, the ndings contribute to the advancement of multimodal skin lesion
analysis by improving the understanding of the role of clinical attributes, proposing more
adaptive fusion strategies, and exploring solutions oriented toward robustness and efficiency
in realistic clinical scenarios.
