Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms by Zhao Chen, Hao Liu, Yao Zhang, Fei Xing, Jiabao Jiang, Zhou Xiang, Zhou Xiang, Xin Duan, Xin Duan

“…However, there is still no prediction model for MDD specifically designed for adults who live alone.ObjectiveThis study aims to investigate the effectiveness of utilizing personal health data in combination with a stacked ensemble machine learning (SEML) technique to detect MDD among adults living alone, seeking to gain insights into the interaction between personal health data and MDD.MethodsOur data originated from the US National Health and Nutrition Examination Survey (NHANES) spanning 2007 to 2018. …”
Get full text

Profiling of gastric cancer cell-surface markers to achieve tumour–normal discrimination by Henry Yang, Khek Yu Ho, Judith Toh, Michal Marek Hoppe, Teena Thakur, Kar Tong Tan, Brendan Pang, Sharmaine Ho, Rony Roy, Khay Guan Yeoh, Raghav Sundar, Anand Jeyasekharan

“…Combined multiplexed imaging of these four markers revealed improved specificity and sensitivity for detection of tumour from normal tissue (AUC of 4-plex=0.91).Conclusion CEAMCAM5, CEACAM6, EpCAM, and CA72-4 form a versatile set of markers for robust discrimination of GC from adjacent normal tissue. …”
Get full text

Early identification of mild cognitive impairment: an innovative model using ocular biomarkers by Lingjing Zhang, Lingjing Zhang, Yanwei Wang, Yuming Liu, Zi Ye, Zhaohui Li

“…This study sought to establish a novel model for early detection of mild cognitive impairment (MCI) in patients with ARC.MethodsThe study prospectively collected 170 monocular data as training dataset and 65 monocular data from another independent medical center as test dataset. …”
Get full text

Prevalence and prenatal diagnosis of major congenital anomalies in Dubai: first insights and emerging patterns in a multicenter cohort study by Anne F. Minsart, Hiba Adam, Nadirah Ghenimi, Muna Tahlak, Fadi G. Mirza, Anjum Akbar, Shanthi Sairam

“…High detection rates were observed in a setting where practitioners come from diverse training backgrounds, and where most patients have risk factors for reduced visibility.…”
Get full text

Snow Depth Extraction From Time‐Lapse Imagery Using a Keypoint Deep Learning Model by C. M. Breen, W. R. Currier, C. Vuyovich, Z. Miao, L. R. Prugh

“…Best performance was achieved when both data sets were included during training, with a MAE of 2.05 cm for Colorado images and a MAE of 1.14 cm for Washington images. …”
Get full text

BIOTHREAT EARLY ASSIST AND RESPONSE COMMAND SYSTEM (BEAR-CS) by Rexhep Mustafovski, Aleksandar Risteski, Tomislav Shuminoski

“…BEAR-CS stands out due to its ability to operate autonomously in high-risk zones, reducing the need for human reconnaissance in dangerous settings. Compared to traditional methods of threat detection, BEAR-CS offers superior speed, data accuracy, and coverage. …”
Get full text

Pulse Wave Generation Method for PPG by Using Display by Atsuhiro Fujii, Kazuya Murao, Naoji Matsuhisa

“…Wearable devices are often used to record the user’s biometric information, and methods have been proposed to detect physical abnormalities from the acquired data. …”
Get full text

Acute Respiratory Distress Identification via Multi-Modality Using Deep Learning by Wajahat Nawaz, Kevin Albert, Philippe Jouvet, Rita Noumeir

“…These findings suggest that multi-modality data provide a promising solution for improving ARD detection accuracy and confidence in clinical settings.…”
Get full text

Dynamic EIT technology for real-time non-invasive monitoring of acute pulmonary embolism: a porcine model experiment by Junyao Li, Mingxu Zhu, Yitong Guo, Weichen Li, Qing He, Yu Wang, Yuxuan Liu, Benyuan Liu, Yang Liu, Weice Wang, Zhenyu Ji, Xuetao Shi

“…This provides a new avenue for the non-invasive real-time monitoring of patients with acute pulmonary embolism in a clinical setting.…”
Get full text

Transforming Alzheimer’s Disease Diagnosis: Implementing Vision Transformer (ViT) for MRI Images Classification by Dian Kurniasari, Muhammad Dwi Pratama, Akmal Junaidi, Ahmad Faisol

“…The ViT model holds great potential for advancing Alzheimer’s diagnosis, offering a valuable tool for early detection and intervention in clinical settings. …”
Get full text

Analytical Validation of Wrist-Worn Accelerometer-Based Step-Count Methods during Structured and Free-Living Activities by Robert T. Marcotte, Shelby L. Bachman, Yaya Zhai, Ieuan Clay, Kate Lyden

“…Methods utilizing peak detection, threshold crossing, and frequency analysis have been used to detect steps from wrist-worn accelerometer data, but it remains unclear how different approaches perform across a range of walking speeds and free-living activities. …”
Get full text

Quantitative study of local defects by pulsed eddy current testing by Zhaoyang Li, Liang Dong

“…This approach ensures that the probe settings are tailored to the specific characteristics of the defects being investigated. …”
Get full text

Educating the digital generation: the role of virtual communities by E. M. Kharlanova, N. V. Sivrikova, S. V. Roslyakova, E. G. Chernikova

“…The authors employed the methods of mathematical data processing: Somers’ D-test, Kramer’s V-test, CHAID (Chi Squared Automatic Interaction Detection) analysis.                …”
Get full text

Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Electronic patient records, containing big data, offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms. …”
Get full text

The First Combined Hα and Rest-UV Spectroscopic Probe of Galactic Outflows at High Redshift by Emily Kehoe, Alice E. Shapley, N. M. Förster Schreiber, Anthony J. Pahl, Michael W. Topping, Naveen A. Reddy, Reinhard Genzel, Sedona H. Price, L. J. Tacconi

“…With this unprecedented data set, we examine the properties of gas flows estimated from LRIS and KMOS in relation to other galaxy properties, such as star formation rate (SFR), SFR surface density (Σ _SFR ), stellar mass ( M _* ), and main-sequence offset (ΔMS). …”
Get full text

Preoperative DBT-based radiomics for predicting axillary lymph node metastasis in breast cancer: a multi-center study by Shuyan He, Biao Deng, Jiaqi Chen, Jiamin Li, Xuefeng Wang, Guanxing Li, Siyu Long, Jian Wan, Yan Zhang

“…Specifically, 390 cases were from one Hospital, and 146 cases were from another Hospital. These data were assigned to internal training and external validation sets, respectively. …”
Get full text

Hyperspectral Imaging for Phenotyping Plant Drought Stress and Nitrogen Interactions Using Multivariate Modeling and Machine Learning Techniques in Wheat by Frank Gyan Okyere, Daniel Kingsley Cudjoe, Nicolas Virlet, March Castle, Andrew Bernard Riche, Latifa Greche, Fady Mohareb, Daniel Simms, Manal Mhada, Malcolm John Hawkesford

“…Accurate detection of drought stress in plants is essential for water use efficiency and agricultural output. …”
Get full text

Point-of-Care Testing (POCT) for Cancer and Chronic Disease Management in the Workplace: Opportunities and Challenges in the Era of Digital Health Passports by Maria Daoutakou, Spyridon Kintzios

“…Concurrently, the development of digital health passports has created secure, dynamic platforms for managing and sharing personal health data. This review explores the technological innovations underpinning POCT, examines its application in workplace health screening, and analyzes how integration with the Internet of Things (IoT) and digital health passports can enhance early detection and chronic disease management. …”
Get full text

Artificial intelligence in occupational health practice by Francesco Chirico, Nicola Magnavita

“…In this viewpoint, the authors explore AI's role in managing health data through natural language processing, aiding physicians in clinical documentation and patient communication. …”
Get full text

A novel deep learning radiopathomics model for predicting carcinogenesis promotor cyclooxygenase-2 expression in common bile duct in children with pancreaticobiliary maljunction: a... by Hui-min Mao, Jian-jun Zhang, Bin Zhu, Wan-liang Guo

“…Methods This retrospective study included 219 PBM patients, divided into a training set (n = 104; median age, 2.8 years, 75.0% females) and internal test set (n = 71; median age, 2.2 years, 83.1% females) from center I, and an external test set (n = 44; median age, 3.4 years, 65.9% females) from center II. …”
Get full text