Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial by Caio César Souza Conceição, Camila Marinelli Martins, Mayck Medeiros Silva, Hugo Caire de Castro Faria Neto, Davide Chiumello, Davide Chiumello, Davide Chiumello, Patricia Rieken Macedo Rocco, Fernanda Ferreira Cruz, Pedro Leme Silva

“…AUCs were compared using DeLong’s algorithm.ResultsOverall, 203 patients were included in the analysis, and they were divided into two groups; clinical improvement (n = 154) and no clinical improvement (n = 49). …”
Get full text

Towards full integration of explainable artificial intelligence in colon capsule endoscopy’s pathway by Esmaeil S. Nadimi, Jan-Matthias Braun, Benedicte Schelde-Olesen, Smith Khare, Vinay C. Gogineni, Victoria Blanes-Vidal, Gunnar Baatrup

“…We developed a family of algorithms based on explainable deep neural networks (DNN) that detect polyps within a sequence of images, feed only those images containing polyps into two parallel independent networks to characterize, and estimate the size of important findings. …”
Get full text

Insights from UKCTOCS for design, conduct and analyses of large randomised controlled trials by Usha Menon, Aleksandra Gentry-Maharaj, Matthew Burnell, Sophia Apostolidou, Andy Ryan, Jatinderpal K Kalsi, Naveena Singh, Lesley Fallowfield, Alistair J McGuire, Stuart Campbell, Steven J Skates, Anne Dawnay, Mahesh Parmar, Ian J Jacobs

“…Significant engagement with participants ensured retention and low rates of complaints. Our solutions to the design, conduct and analyses issues we faced are highly relevant, given the renewed focus on trials for early detection of cancer. …”
Get full text

Adaptive strategies for the deployment of rapid diagnostic tests for COVID-19: a modelling study [version 2; peer review: 2 approved, 1 approved with reservations] by Emily Kendall, Lucia Cilloni, Nimalan Arinaminpathy, David Dowdy

“…Concentrating on urban areas in low- and middle-income countries, the aim of this analysis was to estimate the degree to which ‘dynamic’ screening algorithms, that adjust the use of confirmatory polymerase chain reaction (PCR) testing based on epidemiological conditions, could reduce cost without substantially reducing the impact of testing. …”
Get full text

Optimization of energy acquisition system in smart grid based on artificial intelligence and digital twin technology by Zhen Jing, Qing Wang, Zhiru Chen, Tong Cao, Kun Zhang

“…Abstract In response to the low operating speed and poor stability of energy harvesting systems in smart grids, an energy harvesting optimization method based on improved convolutional neural networks and digital twin technology is proposed in the experiment. …”
Get full text

Using Digital Technology to Conduct COVID-19 Surveillance: A Systematic Review by Fitrisia Rahma, Fatmah Fatmah, Rachmadhi Purwana

“…Key among these are (1) the scarcity of high-quality, unbiased data and the difficulties of integrating disparate datasets; (2) limitations in technology design and the shortage of skilled human resources to develop, deploy, and maintain digital tools; (3) gaps in physical and network infrastructure, particularly in low- and middle-income settings; (4) cybersecurity vulnerabilities and complex ethical quandaries around privacy, consent, and algorithmic transparency; and (5) broader political, social, and environmental barriers, ranging from governance misalignment to inequitable access and ecological impacts. …”
Get full text

Amyloid Cardiomyopathy: Review of A Fatal Case Report by O. V. Soldatova, I. Ya. Goryanskaya

“…Close attention to the problem of amyloid cardiomyopathy in recent years has been caused by a significant increase in the disease detection simultaneously with increased sensitivity and specificity of imaging methods used in cardiological practice, along with the emergence of new promising diagnostic methods and specific therapy. …”
Get full text

Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

“…However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. …”
Get full text

Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…The comprehensive examination of our model revealed substantial variations in clinical and pathological characteristics, enriched pathways, cancer hallmarks, and immune infiltration scores between high-risk and low-risk groups. Wet lab experiments validated the role of KRT6B in NSCLC, demonstrating that KRT6B expression is elevated and it stimulates the proliferation of cancer cells.DiscussionThese observations not only enhance our understanding of metabolic reprogramming and its biological functions in NSCLC but also provide new perspectives for early detection, prognostic evaluation, and targeted therapy. …”
Get full text

Machine Learning Model for Predicting Pathological Invasiveness of Pulmonary Ground‐Glass Nodules Based on AI‐Extracted Radiomic Features by Guozhen Yang, Yuanheng Huang, Huiguo Chen, Weibin Wu, Yonghui Wu, Kai Zhang, Xiaojun Li, Jiannan Xu, Jian Zhang

“…ABSTRACT Background With the widespread adoption of low‐dose CT screening, the detection of pulmonary ground‐glass nodules (GGNs) has risen markedly, presenting diagnostic challenges in distinguishing preinvasive lesions from invasive adenocarcinomas (IAC). …”
Get full text

Eliminating geometric distortion with dual-orbit Sentinel-1 SAR fusion for accurate glacial lake extraction in Southeast Tibet Plateau by Renzhe Wu, Guoxiang Liu, Xin Bao, Jichao Lv, Age Shama, Bo Zhang, Wenfei Mao, Jie Chen, Zhihan Yang, Rui Zhang

“…This method detects low-quality pixels from dual-orbit SAR imagery through geometric distortion. …”
Get full text

Medical Data over Sound—CardiaWhisper Concept by Radovan Stojanović, Jovan Đurković, Mihailo Vukmirović, Blagoje Babić, Vesna Miranović, Andrej Škraba

“…Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications.…”
Get full text

Integrating transcriptomics and hybrid machine learning enables high-accuracy diagnostic modeling for nasopharyngeal carcinoma by Hehe Wang, Junge Zhang, Peng Cheng, Lujie Yu, Chunlin Li, Yaowen Wang

“…The findings provide a scalable framework for early NPC detection and novel insights into immune microenvironment dysregulation.…”
Get full text

CELIAC DISEASE SCREENING IN A LARGE DOWN SYNDROME COHORT: COMPARISON OF DIAGNOSTIC YIELD OF DIFFERENT SEROLOGICAL SCREENING TESTS by Dilek Uludağ Alkaya, Seçil Sözen, Birol Öztürk, Nuray Kepil, Tülay Erkan, Hüseyin Tufan Kutlu, Beyhan Tüysüz

“…Conclusion: Celiac disease was detected in 2.3% of DS patients. The CD detection rate was 1.3% at initial screening but increased to 4.9% at rescreening. …”
Get full text

SPYDER: QoS-Aware Radio Resource Allocation in Multiuser ISAC-Capable C-V2X Networks by Syed Najaf Haider Shah, Aamir Ullah Khan, Christian Schneider, Joerg Robert

“…Since SPYDER adopts a non-uniform TF interleaved OFDM grid, it may experience multiuser resource overlapping that could degrade radar detection performance. To counteract this, we employ sparse reconstruction algorithms within the compressed sensing framework, enhancing flexibility in TF resource allocation and providing high-resolution radar sensing despite uncoordinated resource selection. …”
Get full text

Limitations of using artificial intelligence services to analyze chest x-ray imaging by Yuriy A. Vasilev, Anton V. Vladzymyrskyy, Kirill M. Arzamasov, Igor M. Shulkin, Elena V. Astapenko, Lev D. Pestrenin

“…Among false-negative cases, the rate of overlooked clinically significant pathology was low, which accounted for less than one-fourth.…”
Get full text

Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Three models were developed: (1) R model: radiomics-based machine learning (ML) algorithms; (2) CNN model: image-based CNN algorithms; (3) DLR model: a hybrid model combining radiomics and deep learning features with ML algorithms. …”
Get full text

Digital Colorimetry of Non-steroidal Anti-inflammatory Drugs: Identification Using Principal Component Method by A. A. Chaplenko, O. V. Monogarova, K. V. Oskolok

“…Digital colorimetry is one of the available and simple methods that can be used for the rapid detection of low-quality drugs. The main limitation of the method is its lack of selectivity. …”
Get full text

Exposure and infection to Plasmodium knowlesi in case study communities in Northern Sabah, Malaysia and Palawan, The Philippines. by Kimberly M Fornace, Lou S Herman, Tommy R Abidin, Tock Hing Chua, Sylvia Daim, Pauline J Lorenzo, Lynn Grignard, Nor Afizah Nuin, Lau Tiek Ying, Matthew J Grigg, Timothy William, Fe Espino, Jonathan Cox, Kevin K A Tetteh, Chris J Drakeley

Get full text

Radiomic study on preoperative multi‐modal magnetic resonance images identifies IDH‐mutant TERT promoter‐mutant gliomas by Haoyu Wang, Shuxin Zhang, Xiang Xing, Qiang Yue, Wentao Feng, Siliang Chen, Jun Zhang, Dan Xie, Ni Chen, Yanhui Liu

“…A diagnostic model (multilayer perceptron classifier) for detecting the IDHmut pTERTmut gliomas was trained using an automatic machine‐learning algorithm named tree‐based pipeline optimization tool (TPOT). …”
Get full text