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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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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Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…Consequently, for early-stage BC, timely screening, accurate diagnosis, and the development of personalized treatment strategies are crucial for enhancing patient survival rates. …”
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Artificial intelligence in molecular and genomic prostate cancer diagnostics by A. O. Morozov, A. K. Bazarkin, S. V. Vovdenko, M. S. Taratkin, M. S. Balashova, D. V. Enikeev

“…They have the potential to develop artificial intelligence (AI) algorithms by processing large amounts of data and define connections between them.Objective. …”
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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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Enhancing Stroke Prediction with Logistic Regression and Support Vector Machine Using Oversampling Techniques by Syamsul Risal, Fajar Apriyadi, A. Sumardin, Andini Dani Achmad, Annisa Nurul Puteri

“…Simultaneously, SVM with Borderline-SMOTE may be more appropriate for resource-constrained environments.…”
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Design and validation of a novel multiple sites signal acquisition and analysis system based on pressure stimulation for human cardiovascular information by Gaiqin Liu, Yuan Li, Longcong Chen, Juan Jiang, Jie Tian, Panpan Feng

“…Therefore, it is crucial to maximize the acquisition of cardiovascular information (CVI) through non-invasive methods to enhance early screening, diagnosis, and evaluation of CVDs. Numerous studies have demonstrated that obtaining more CVI by simultaneously acquiring multi-site signals and applying pressure stimulation at specific sites, such as blood pressure measurement, is an effective approach. …”
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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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Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

“…The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules by Zhi Li, Wenjing Zhang, Jinyi Huang, Ling Lu, Dongming Xie, Jinrong Zhang, Jiamin Liang, Yuepeng Sui, Linyuan Liu, Jianjun Zou, Ao Lin, Lei Yang, Fuman Qiu, Zhaoting Hu, Mei Wu, Yibin Deng, Xin Zhang, Jiachun Lu

“…Currently, more than 90% of PNs detected by screening tests are benign, with a false positive rate of up to 96.4%. …”
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Research on implementation of interventions in tuberculosis control in low- and middle-income countries: a systematic review. by Frank Cobelens, Sanne van Kampen, Eleanor Ochodo, Rifat Atun, Christian Lienhardt

“…Evaluations of diagnostic and screening algorithms were more frequent (n = 19) but geographically clustered and mainly of non-comparative design. …”
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Association between Alzheimer's disease pathologic products and age and a pathologic product-based diagnostic model for Alzheimer's disease by Weizhe Zhen, Yu Wang, Hongjun Zhen, Weihe Zhang, Wen Shao, Yu Sun, Yanan Qiao, Shuhong Jia, Zhi Zhou, Yuye Wang, Leian Chen, Jiali Zhang, Dantao Peng, Dantao Peng

“…In the non-AD group, the trend of pathologic product levels with age was consistently opposite to that of the AD group. We finally screened the optimal AD diagnostic model (AUC=0.959) based on the results of correlation analysis and by using the Xgboost algorithm and SVM algorithm.ConclusionIn a novel finding, we observed that Tau protein and Aβ had opposite trends with age in both the AD and non-AD groups. …”
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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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Auxiliary Diagnosis of Breast Cancer Based on Machine Learning and Hybrid Strategy by Hua Chen, Kehui Mei, Yuan Zhou, Nan Wang, Guangxing Cai

“…Then, the features of the dataset are initially screened using the mutual information method, and further secondary feature selection is performed using the recursive feature elimination method based on the XGBoost algorithm. …”
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Risk Assessment of High-Voltage Power Grid Under Typhoon Disaster Based on Model-Driven and Data-Driven Methods by Xiao Zhou, Jiang Li

“…As global warming continues to intensify, typhoon disasters will more frequently occur in East and Southeast Asia, posing a high risk of causing large-scale power outages in the power system. …”
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Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review by Suhila Sawesi, Arya Jadhav, Bushra Rashrash

“…The review identified frequent use of algorithms such as support vector machines, artificial neural networks, decision trees, and convolutional neural networks (CNNs). …”
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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Despite these innovations, challenges such as data privacy, algorithmic bias, and the need for clinical validation remain. …”
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Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

“…Insomnia, the most prevalent sleep disorder, requires more effective diagnosis and screening for proper treatment. …”
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