Results 21 to 30 of about 59,772 (269)

Evaluation of sweating responses in patients with systemic connective tissue disorders using the quantitative sudomotor axon reflex test

Journal of Cutaneous Immunology and Allergy, Volume 5, Issue 6, Page 208-216, December 2022., 2022
We investigated 85 patients on the relationship between the axon reflex sweat volume or the reaction time and Raynaud's phenomenon, skin symptoms and patient background. Most patients did not show a decrease in sweating, but one in three patients showed less sweating in summer than in winter.
Miwa Ashida, Shimpei Morimoto, Mariko Yozaki, Daisuke Ehara, Yuta Koike, Hiroyuki Murota   +5 more
wiley   +1 more source

Immune checkpoint inhibitor-associated toxicity in advanced non-small cell lung cancer: An updated understanding of risk factors

Frontiers in Immunology, 2023
Immune checkpoint inhibitors (ICIs), such as programmed death-1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T lymphocyte antigen 4 (CTLA-4) antibodies, etc, have revolutionized cancer treatment strategies, including non-small cell lung cancer ...
Xiangxiao Hu, Xiangxiao Hu, Xiangxiao Hu, Lina Wang, Lina Wang, Lina Wang, Lina Wang, Bin Shang, Junren Wang, Junren Wang, Junren Wang, Jian Sun, Jian Sun, Jian Sun, Bin Liang, Bin Liang, Bin Liang, Lili Su, Lili Su, Lili Su, Wenjie You, Wenjie You, Wenjie You, Wenjie You, Shujuan Jiang, Shujuan Jiang, Shujuan Jiang   +26 more
doaj   +1 more source

A cytotoxic survey on 2‐amino‐1H‐imidazol based synthetic marine sponge alkaloid analogues

Drug Development Research, Volume 83, Issue 8, Page 1906-1922, December 2022., 2022
Abstract Here, we describe the synthesis and biologic activity evaluation of 20 novel synthetic marine sponge alkaloid analogues with 2‐amino‐1H‐imidazol (2‐AI) core. Cytotoxicity was tested on murine 4T1 breast cancer, A549 human lung cancer, and HL‐60 human myeloid leukemia cells by the resazurin assay.
Nikolett Gémes, Zsófia Makra, Patrícia Neuperger, Enikő Szabó, József Á. Balog, Lili Borbála Flink, Beáta Kari, László Hackler Jr, László. G. Puskás, Iván Kanizsai, Gábor J. Szebeni   +10 more
wiley   +1 more source

Towards Reliable Dermatology Evaluation Benchmarks [PDF]

Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:101-128, 2023, 2023
Benchmark datasets for digital dermatology unwittingly contain inaccuracies that reduce trust in model performance estimates. We propose a resource-efficient data-cleaning protocol to identify issues that escaped previous curation. The protocol leverages an existing algorithmic cleaning strategy and is followed by a confirmation process terminated by ...
arxiv  

Disparities in Dermatology AI: Assessments Using Diverse Clinical Images [PDF]

, 2021
More than 3 billion people lack access to care for skin disease. AI diagnostic tools may aid in early skin cancer detection; however most models have not been assessed on images of diverse skin tones or uncommon diseases. To address this, we curated the Diverse Dermatology Images (DDI) dataset - the first publicly available, pathologically confirmed ...
arxiv   +1 more source

Mouse dendritic cells and other myeloid subtypes in healthy lymph nodes and skin: 26‐Color flow cytometry panel for immune phenotyping

European Journal of Immunology, Volume 52, Issue 12, Page 2006-2009, December 2022., 2022
This novel 26‐color flow cytometry panel allows the detailed immune phenotyping of the complex network of myeloid cells in murine lymph nodes and skin. With the optimized panel the different murine DC‐subsets and other myeloid cell types can be identified and further characterized for co‐stimulatory and inhibitory surface molecules.
Florian Hornsteiner, Martina M Sykora, Christoph H Tripp, Sieghart Sopper, Patrizia Stoitzner   +4 more
wiley   +1 more source

Towards Realization of Augmented Intelligence in Dermatology: Advances and Future Directions [PDF]

arXiv, 2021
Artificial intelligence (AI) algorithms using deep learning have advanced the classification of skin disease images; however these algorithms have been mostly applied "in silico" and not validated clinically. Most dermatology AI algorithms perform binary classification tasks (e.g.
arxiv  

Joint Dermatological Lesion Classification and Confidence Modeling with Uncertainty Estimation [PDF]

arXiv, 2021
Deep learning has played a major role in the interpretation of dermoscopic images for detecting skin defects and abnormalities. However, current deep learning solutions for dermatological lesion analysis are typically limited in providing probabilistic predictions which highlights the importance of concerning uncertainties.
arxiv  

Empirical comparison of routinely collected electronic health record data for head and neck cancer‐specific survival in machine‐learnt prognostic models

Head &Neck, Volume 45, Issue 2, Page 365-379, February 2023., 2023
Abstract Background Knowledge of the prognostic factors and performance of machine learning predictive models for 2‐year cancer‐specific survival (CSS) is limited in the head and neck cancer (HNC) population. Methods Data from our facilities' oncology information system (OIS) collected for routine practice (OIS dataset, n = 430 patients) and research ...
Damian P. Kotevski, Robert I. Smee, Claire M. Vajdic, Matthew Field   +3 more
wiley   +1 more source

Guselkumab in Patients with Scalp Psoriasis: A post hoc Analysis of the VOYAGE 2 Phase III Randomized Clinical Trial

Acta Dermato-Venereologica
Scalp psoriasis affects approximately 80% of patients with psoriasis and can negatively impact their quality of life. This post hoc analysis of the VOYAGE 2 Phase III randomized clinical trial evaluated scalp response to guselkumab treatment and its ...
Enikö Sonkoly, Julia-Tatjana Maul, Matteo Megna, Patricia Gorecki, Edmée Crombag, Jozefien Buyze, Laura Savage   +6 more
doaj   +1 more source