Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…As a consequence of this conversion, breast tumors with anomalies become more visible, which allows us to extract more accurate features about them. …”
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Predicting cardiotoxicity in drug development: A deep learning approach by Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han

“…This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment. …”
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Deep Learning Classification of Systemic Sclerosis Skin Using the MobileNetV2 Model by Metin Akay, Yong Du, Cheryl L. Sershen, Minghua Wu, Ting Y. Chen, Shervin Assassi, Chandra Mohan, Yasemin M. Akay

“…Additionally, it took more than 14 hours to train the CNN architecture. …”
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Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis by Weifeng Yang, Xiaohua Wu, Jian Wang, Wenquan Ou, Xing Huang

“…Three machine learning algorithms identified distinct sets of prognostic genes in gastric cancer patients. …”
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Identification of specific metabolic pathways as druggable targets regulating the sensitivity to cyanide poisoning. by Patrick Y Sips, Xu Shi, Gabriel Musso, Anjali K Nath, Yanbin Zhao, Jason Nielson, Jordan Morningstar, Amy E Kelly, Brittney Mikell, Eva Buys, Vikhyat Bebarta, Jared Rutter, V Jo Davisson, Sari Mahon, Matthew Brenner, Gerry R Boss, Randall T Peterson, Robert E Gerszten, Calum A MacRae

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Canadian Thoracic Society Recommendations for Management of Chronic Obstructive Pulmonary Disease – 2008 Update – Highlights for Primary Care by Denis E O’Donnell, Paul Hernandez, Alan Kaplan, Shawn Aaron, Jean Bourbeau, Darcy Marciniuk, Meyer Balter, Gordon Ford, Andre Gervais, Yves Lacasse, Francois Maltais, Jeremy Road, Graeme Rocker, Don Sin, Tasmin Sinuff, Nha Voduc

“…Three key messages contained in the update are: use targeted screening spirometry to establish a diagnosis and initiate prompt management (including smoking cessation) of mild COPD; improve dyspnea and activity limitation in stable COPD using new evidence-based treatment algorithms; and understand the importance of preventing and managing acute exacerbations, particularly in moderate to severe disease.…”
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Assessing the causal effect of inflammation‐related genes on myocarditis: A Mendelian randomization study by Huazhen Xiao, Hongkui Chen, Wenjia Liang, Yucheng Liu, Kaiyang Lin, Yansong Guo

“…The GWAS data (finn‐b‐I9 MYOCARD) contained single nucleotide polymorphisms (SNPs) data from 117 755 myocarditis samples (16 379 455 SNPs, 829 cases vs. 116 926 controls). Five algorithms [MR‐Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode regression] were employed for the MR analysis, with IVW as the primary method, and sensitivity analysis was conducted. …”
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The clinical utility and safety of biomarker-guided immunosuppression withdrawal in liver transplantation: the LIFT prospective RCT by Julien Vionnet, Rosa Miquel, Juan G Abraldes, Juan-Jose Lozano, Pablo Ruiz, Miquel Navasa, Aileen Marshall, Frederik Nevens, William Gelson, Joanna Leithead, Steven Masson, Elmar Jaeckel, Richard Taubert, Phaedra Tachtatzis, Dennis Eurich, Kenneth Simpson, Eliano Bonaccorsi-Riani, James Ferguson, Alberto Quaglia, Maria Elstad, Marc Delord, Abdel Douiri, Alberto Sánchez-Fueyo

“…This was done by enrolling patients more than 3 years after transplantation and allocating them at random to two groups. …”
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Prevalence of tuberculosis, HIV and respiratory symptoms in two Zambian communities: implications for tuberculosis control in the era of HIV. by Helen Ayles, Albertus Schaap, Amos Nota, Charalambos Sismanidis, Ruth Tembwe, Petra De Haas, Monde Muyoyeta, Nulda Beyers, Peter Godfrey-Faussett for the ZAMSTAR Study Team

“…Epidemiological studies can inform screening algorithms for both detection and prevention of active tuberculosis.…”
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TikTok and Sound: Changing the ways of Creating, Promoting, Distributing and Listening to Music by Bojana Radovanović

“…In this article I will explore the ways in which TikTok has made an “aural turn” (Abidin and Kaye 2021), and thus changed and influenced the processes of music-making, music listening and music promotion. …”
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Peripherex Home Visual Field Demonstrates High Test-Retest Reliability, Validity by Schweitzer J, Ibach M, Berdahl J, Daoud M, Daoud YA, Kempinski Y, Goldberg JL

“…These data support in-home use of the PRX VFT by the eye care provider for screening and monitoring in glaucoma, and may be extended to the screening and monitoring of other retinal, optic nerve and neurological diseases.Keywords: visual field test, glaucoma, home healthcare, prospective clinical trial…”
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Unlocking the bottleneck in forward genetics using whole-genome sequencing and identity by descent to isolate causative mutations. by Katherine R Bull, Andrew J Rimmer, Owen M Siggs, Lisa A Miosge, Carla M Roots, Anselm Enders, Edward M Bertram, Tanya L Crockford, Belinda Whittle, Paul K Potter, Michelle M Simon, Ann-Marie Mallon, Steve D M Brown, Bruce Beutler, Christopher C Goodnow, Gerton Lunter, Richard J Cornall

“…Analysis of the IBD regions also allows us to calculate the ENU mutation rate (1.54 mutations per Mb) and to model future strategies for genetic screens in mice. The introduction of this approach will accelerate the discovery of causal variants, permit broader and more informative lethal screens to be used, reduce animal costs, and herald a new era for ENU mutagenesis.…”
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In the Refractory Hypertension “Labyrinth”. Focus on Primary Hyperaldosteronism by O. V. Tsygankova, T. I. Batluk, L. D. Latyntseva, E. V. Akhmerova, N. M. Akhmedzhanov

“…It should not only have made the diagnosis easy, but it could have also absolutely justified the surgical tactics. …”
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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…Existing gaps include data quality, algorithmic transparency, and ethical concerns around privacy, among others. …”
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Robustness evaluation of commercial liveness detection platform by Pengcheng WANG, Haibin ZHENG, Jianfei ZOU, Ling PANG, Hu LI, Jinyin CHEN

“…Liveness detection technology has become an important application in daily life, and it is used in scenarios including mobile phone face unlock, face payment, and remote authentication.However, if attackers use fake video generation technology to generate realistic face-swapping videos to attack the living body detection system in the above scenarios, it will pose a huge threat to the security of these scenarios.Aiming at this problem, four state-of-the-art Deepfake technologies were used to generate a large number of face-changing pictures and videos as test samples, and use these samples to test the online API interfaces of commercial live detection platforms such as Baidu and Tencent.The test results show that the detection success rate of Deepfake images is generally very low by the major commercial live detection platforms currently used, and they are more sensitive to the quality of images, and the false detection rate of real images is also high.The main reason for the analysis may be that these platforms were mainly designed for traditional living detection attack methods such as printing photo attacks, screen remake attacks, and silicone mask attacks, and did not integrate advanced face-changing detection technology into their liveness detection.In the algorithm, these platforms cannot effectively deal with Deepfake attacks.Therefore, an integrated live detection method Integranet was proposed, which was obtained by integrating four detection algorithms for different image features.It could effectively detect traditional attack methods such as printed photos and screen remakes.It could also effectively detect against advanced Deepfake attacks.The detection effect of Integranet was verified on the test data set.The results show that the detection success rate of Deepfake images by proposed Integranet detection method is at least 35% higher than that of major commercial live detection platforms.…”
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Development and application of an early prediction model for risk of bloodstream infection based on real-world study by Xiefei Hu, Shenshen Zhi, Yang Li, Yuming Cheng, Haiping Fan, Haorong Li, Zihao Meng, Jiaxin Xie, Shu Tang, Wei Li

“…During the feature selection stage, univariate regression and ML algorithms were applied. First, Univariate logistic regression was used to screen for predictive factors of BSI. …”
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Predicting the generalization of computer aided detection (CADe) models for colonoscopy by Joel Shor, Carson McNeil, Yotam Intrator, Joseph R. Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

“…Abstract Generalizability of AI colonoscopy algorithms is important for wider adoption in clinical practice. …”
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Cysticercosis in Madagascar by Jean-François Carod, Pierre Dorny

“…Neurocysticercosis (NCC) is the most common pattern of cysticercosis in Madagascar and it is reponsible for pediatric morbidity causing more than 50% of epilepsy cases. Though CT-Scan is now available and tends to be considered the gold standard for NCC diagnosis, it remains unaffordable for most Malagasy patients and implies the proposal of a diagnostic algorithm for physicians. …”
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A Cell Component-Related Prognostic Signature for Head and Neck Squamous Cell Carcinoma Based on the Tumor Microenvironment by Siyu Li, Yajun Gu, Junguo Wang, Dengbin Ma, Xiaoyun Qian, Xia Gao

“…In this study, we aimed to develop a cell component-related prognostic model based on TME. We screened cell component enrichments from samples in The Cancer Genome Atlas (TCGA) HNSCC cohort using the xCell algorithm. …”
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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…Hence, the development of efficient automated DR grading systems is crucial for early screening and treatment. Although progress has been made in DR detection using deep learning techniques, these methods still face challenges in handling the complexity of DR lesion characteristics and the nuances in grading criteria. …”
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