Results 71 to 80 of about 7,877,596 (288)

Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy

Molecular Oncology, EarlyView.
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen, Zhi Zhao, Henrik Horndalsveen, Maria Moksnes Bjaanæs, Bjørn Henning Grønberg, Tarje Halvorsen, Tesfaye Madebo, Marianne Aanerud, Jussi Koivunen, Kersti Oselin, Saulius Cicenas, Nina Helbekkmo, Jarkko Ahvonen, Maria Silvoniemi, Tine Norman Alver, Tonje Dalen, Åsa Kristina Öjlert, Saima Jamil Farooqi, Åslaug Helland, Vilde Drageset Haakensen   +19 more
wiley   +1 more source

A trajectory data publishing algorithm satisfying local suppression

International Journal of Distributed Sensor Networks, 2021
Suppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data.
Xiaohui Li, Yuliang Bai, Yajun Wang, Bo Li   +3 more
doaj   +1 more source

Spatial heterogeneity of hotspot mutations and clonal relatedness in ovarian endometrioid carcinoma

Molecular Oncology, EarlyView.
Spatially resolved analysis revealed heterogeneous distributions of selected cancer‐associated mutations within ovarian endometrioid carcinomas. Shared mutations between paired endometrial and ovarian tumors supported clonal relatedness. These findings highlight the value of sampling multiple tumor regions when interpreting molecular profiles ...
Takahito Ashihara, Kosuke Murakami, Shiro Takamatsu, Akiko Kanto, Seiichi Mori, Tomoyuki Otani, Kazuko Sakai, Yasushi Kotani, Kazuto Nishio, Kaoru Abiko, Noriomi Matsumura   +10 more
wiley   +1 more source

Advancements in Gaussian and Local Differential Privacy [PDF]

, 2023
This thesis presents a comprehensive study of Gaussian Differential Privacy (GDP) and Local Differential Privacy (LDP), exploring their properties, relationships, and applications in developing novel algorithms and optimization methods for efficient and ...
Liu, Yi
core   +1 more source

Study on utility optimization for randomized response mechanism

Tongxin xuebao, 2019
For the study of privacy-utility trade-off in local differential privacy,the utility optimization models of binary generalized random response mechanism for the case of differential privacy and approximate differential privacy were established.By graphic
Yihui ZHOU, Laifeng LU, Zhenqiang WU
doaj   +2 more sources

Enhancing Metric Privacy With a Shuffler

International audienceDifferential Privacy (DP) is one of the most successful privacy-preserving frameworks. In the central model of DP a trusted server adds controlled noise as it acts as an interface between the data providers (users) and the data ...
Chatzikokolakis, Konstantinos, Athanasiou, Andreas, Palamidessi, Catuscia   +2 more
core   +6 more sources

trasgoDP: An open source framework for releasing noised tabular microdata under local differential privacy

SoftwareX
This paper presents trasgoDP , a modular Python framework for releasing tabular microdata under record-level local differential privacy guarantees.
J. Sáinz-Pardo Díaz, Á. López García   +1 more
doaj   +1 more source

Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up

Molecular Oncology, EarlyView.
This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani, Laura Mariën, Caro De Weerdt, Sanne Wouters, Laure‐Anne Teuwen, Hans Prenen, Katleen Janssens, Timon Vandamme   +7 more
wiley   +1 more source

From patient advocacy to patient‐driven research: Building active partnerships beginning at the bench to reach the bedside

FEBS Open Bio, EarlyView.
Research is strongest when conducted alongside patients, not just about them. Patient research organizations help integrate patient perspectives into research priorities, study design, and scientific meetings, leading to meaningful patient outcomes and development of relevant therapies.
Jenica H. Kakadia, Rachel Heilmann, Maximiliano Barrientos, Laura MacNeill, Ingrid Vallee, Sarah K. Schultz, Patrick O'Donoghue, Angelica A. Moresco, Victoria M. Siu, Ilka U. Heinemann   +9 more
wiley   +1 more source

Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Proceedings 2022 Network and Distributed System Security Symposium, 2022
Federated Learning (FL) allows multiple participants to train machine learning models collaboratively by keeping their datasets local while only exchanging model updates. Alas, this is not necessarily free from privacy and robustness vulnerabilities, e.g., via membership, property, and backdoor attacks.
Mohammad Naseri, Jamie Hayes, Emiliano De Cristofaro   +2 more
openaire   +3 more sources