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Record W4406738700 · doi:10.1097/dss.0000000000004542

The History and Advancement of Light, Lasers, and Energy-Based Devices in Dermatologic Surgery

2025· review· en· W4406738700 on OpenAlexaff
Jeffrey S. Dover, Chaocheng Liu, Jacqueline Watchmaker, Jordan V. Wang, Roy G. Geronemus, Kenneth A. Arndt, R. Rox Anderson

Bibliographic record

VenueDermatologic Surgery · 2025
Typereview
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineHair removalIntense pulsed lightDermatologyDermatologic surgeryLaserLaser surgeryAcneEnergy densityPhotodynamic therapySurgeryMedical physicsEngineering physicsOptics

Abstract

fetched live from OpenAlex

BACKGROUND: From the theoretical foundations of laser and energy-based applications for the skin to the development of advanced medical devices, the field of dermatologic surgery has undergone transformative changes. OBJECTIVE: To review the scientific and clinical advancement of laser and energy-based therapies within dermatologic surgery. MATERIALS AND METHODS: A literature search was conducted to identify important scientific advancements and landmark studies on light, laser, and energy-based devices within the field of dermatologic surgery. RESULTS: Since the introduction of selective photothermolysis principles in the 1980s, numerous laser and energy-based devices have been developed to effectively treat vascular lesions, target pigmentation, remove tattoos, rejuvenate the skin, and remove hair. Beyond aesthetic applications, photodynamic therapy was introduced to treat various neoplastic and inflammatory conditions. Lasers have also been employed to enhance transcutaneous drug delivery, and new lasers continue to emerge for treating common inflammatory conditions, such as acne. These innovations have contributed to a paradigm shift toward safe and effective, but less invasive, procedure-based treatment in addressing medical and aesthetic concerns in dermatology. CONCLUSION: Dermatologists have consistently led the way in the continuous development and innovative application of laser and energy-based devices to effectively address a variety of skin conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.325
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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