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Prediction of severe preeclampsia in machine learning

Medicine in Novel Technology and Devices 2022年第3期15卷 148-153页

作者： Xinyuan Zhang Yu Chen Stephen Salerno Yi Li Libin Zhou Xiaoxi Zeng Huafeng Li Department of Applied Mechanics College of Architecture and EnvironmentSichuan Province Biomechanical Engineering LaboratorySichuan UniversityChengdu610065SichuanChina Department of Biostatistics University of MichiganAnn ArborMIUSA Medical Big Data Center Sichuan UniversityChengdu610065SichuanChina Department of Computer Science University of WisconsinMadisonWIUSA West China Second University Hospital Sichuan UniversityChengdu610041China Department of Applied Mechanics Sichuan UniversityChengdu610065SichuanChina

This study aimed to find out the blood data characteristics of patients and explore the correlation between severe preeclampsia and blood index *** assistance for the early attention direction of severe preeclampsia diagnosis and treatment.19,653 pregnant women presenting to the West China Second University Hospital,Sichuan University from January 2017 to April *** screening,a total of 248 patients,124 severe preeclampsia cases,and 124 controls were selected for this ***-three blood examination variables were obtained from routine blood work,hepatic,renal and coagulation function *** gradient boosting machine(light GBM),decision tree and random forest were used for date *** randomly divided 35%of the original data as a testing set to conduct internal validation of the performance of the prediction *** area under receiver operating characteristic curve(AUC)was used as the main score to compare the three ***,a binary classification light GBM model based on aspartate aminotransferase,direct bilirubin and activated partial thromboplastin time ratio can predict severe preeclampsia with sensitivity of 88.37%,specificity of 77.27%,AUC of 89.74%and positive predictive value of 65.96%.We believe relevant quantifiable indicators can establish an effective prediction model,which can provide guidance for early detection and prevention of severe preeclampsia.

关键词： Preeclampsia Screening Prediction Blood examination Data characteristics

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Learning Probabilistic Coordinate Fields for Robust Correspondences

arXiv

引用

arXiv 2023年

作者： Zhao, Weiyue Lu, Hao Ye, Xinyi Cao, Zhiguo Li, Xin Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Lane Department of Computer Science and Electrical Engineering West Virginia University MorgantownWV26506-6109 United States

We introduce Probabilistic Coordinate Fields (PCFs), a novel geometric-invariant coordinate representation for image correspondence problems. In contrast to standard Cartesian coordinates, PCFs encode coordinates in correspondence-specific barycentric coordinate systems (BCS) with affine invariance. To know when and where to trust the encoded coordinates, we implement PCFs in a probabilistic network termed PCF-Net, which parameterizes the distribution of coordinate fields as Gaussian mixture models. By jointly optimizing coordinate fields and their confidence conditioned on dense flows, PCF-Net can work with various feature descriptors when quantifying the reliability of PCFs by confidence maps. An interesting observation of this work is that the learned confidence map converges to geometrically coherent and semantically consistent regions, which facilitates robust coordinate representation. By delivering the confident coordinates to keypoint/feature descriptors, we show that PCF-Net can be used as a plug-in to existing correspondence-dependent approaches. Extensive experiments on both indoor and outdoor datasets suggest that accurate geometric invariant coordinates help to achieve the state of the art in several correspondence problems, such as sparse feature matching, dense image registration, camera pose estimation, and consistency filtering. Further, the interpretable confidence map predicted by PCF-Net can also be leveraged to other novel applications from texture transfer to multi-homography classification. Copyright © 2023, The Authors. All rights reserved.

关键词： Textures

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PAL: Prompting Analytic Learning with Missing Modality for Multi-Modal Class-Incremental Learning

arXiv

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arXiv 2025年

作者： Yue, Xianghu Chen, Yiming Zhang, Xueyi Gao, Xiaoxue Feng, Mengling Lao, Mingrui Zhuang, Huiping Li, Haizhou Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China Institute for Infocomm Research A*STAR 138632 Singapore Saw Swee Hock School of Public Health National University of Singapore 117583 Singapore Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangdong Guangzhou510006 China Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Shenzhen518172 China Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore

Multi-modal class-incremental learning (MMCIL) seeks to leverage multi-modal data, such as audio-visual and image-text pairs, thereby enabling models to learn continuously across a sequence of tasks while mitigating forgetting. While existing studies primarily focus on the integration and utilization of multi-modal information for MMCIL, a critical challenge remains: the issue of missing modalities during incremental learning phases. This oversight can exacerbate severe forgetting and significantly impair model performance. To bridge this gap, we propose PAL, a novel exemplar-free framework tailored to MMCIL under missing-modality scenarios. Concretely, we devise modality-specific prompts to compensate for missing information, facilitating the model to maintain a holistic representation of the data. On this foundation, we reformulate the MMCIL problem into a Recursive Least-Squares task, delivering an analytical linear solution. Building upon these, PAL not only alleviates the inherent under-fitting limitation in analytic learning but also preserves the holistic representation of missing-modality data, achieving superior performance with less forgetting across various multi-modal incremental scenarios. Extensive experiments demonstrate that PAL significantly outperforms competitive methods across various datasets, including UPMC-Food101 and N24News, showcasing its robustness towards modality absence and its anti-forgetting ability to maintain high incremental accuracy. © 2025, CC BY.

关键词： Contrastive Learning

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Comments on "Transient Magnetic Shielding of a Planar Conductive Thin Screen via Exact Image Theory"

TechRxiv

引用

TechRxiv 2023年

作者： Štumpf, Martin The Lerch Laboratory of EM Research Department of Radio Electronics FEEC Brno University of Technology Technická 3082/12 Brno616 00 Czech Republic The Department of Computer Science Electrical and Space Engineering EISLAB Luleå University of Technology Luleå971 87 Sweden

关键词： Transient analysis

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Visualizations of Complex Sequences of Family-Infant Vocalizations Using Bag-of-Audio-Words Approach Based on Wav2vec 2.0 Features

arXiv

引用

arXiv 2022年

作者： Li, Jialu Hasegawa-Johnson, Mark McElwain, Nancy L. Department of Electrical and Computer Engineering University of Illinois United States Beckman Institute for Advanced Science and Technology University of Illinois United States Department of Human Development and Family Studies University of Illinois United States

In the U.S., approximately 15-17% of children 2-8 years of age are estimated to have at least one diagnosed mental, behavioral or developmental disorder. However, such disorders often go undiagnosed, and the ability to evaluate and treat disorders in the first years of life is limited. To analyze infant developmental changes, previous studies have shown advanced ML models excel at classifying infant and/or parent vocalizations collected using cell phone, video, or audio-only recording device like LENA. In this study, we pilot test the audio component of a new infant wearable multi-modal device that we have developed called LittleBeats (LB). LB audio pipeline is advanced in that it provides reliable labels for both speaker diarization and vocalization classification tasks, compared with other platforms that only record audio and/or provide speaker diarization labels. We leverage wav2vec 2.0 to obtain superior and more nuanced results with the LB family audio stream. We use a bag-of-audio-words method with wav2vec 2.0 features to create high-level visualizations to understand family-infant vocalization interactions. We demonstrate that our high-quality visualizations capture major types of family vocalization interactions, in categories indicative of mental, behavioral, and developmental health, for both labeled and unlabeled LB audio. Copyright © 2022, The Authors. All rights reserved.

关键词： Visualization

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Learning Certifiably Robust Controllers Using Fragile Perception

arXiv

引用

arXiv 2022年

作者： Sun, Dawei Musavi, Negin Dullerud, Geir Shakkottai, Sanjay Mitra, Sayan Coordinated Science Laboratory University of Illinois UrbanaIL61801 United States The Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States

Advances in computer vision and machine learning enable robots to perceive their surroundings in powerful new ways, but these perception modules have well-known fragilities. We consider the problem of synthesizing a safe controller that is robust despite perception errors. The proposed method constructs a state estimator based on Gaussian processes with input-dependent noises. This estimator computes a high-confidence set for the actual state given a perceived state. Then, a robust neural network controller is synthesized that can provably handle the state uncertainty. Furthermore, an adaptive sampling algorithm is proposed to jointly improve the estimator and controller. Simulation experiments, including a realistic vision-based lane keeping example in CARLA, illustrate the promise of the proposed approach in synthesizing robust controllers with deep-learning-based perception. © 2022, CC BY.

关键词： Controllers

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A 3D Continuous-Space Electromagnetic Channel Model for 6G Tri-Polarized Multi-user Communications

arXiv

引用

arXiv 2025年

作者： Yang, Yue Wang, Cheng-Xiang Huang, Jie Thompson, John Vincent Poor, H. The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The Purple Mountain Laboratories Nanjing211111 China The Institute for Digital Communications School of Engineering University of Edinburgh EdinburghEH9 3JL United Kingdom The Department of Electrical and Computer Engineering Princeton University PrincetonNJ United States

It is envisioned that the sixth generation (6G) and beyond 6G (B6G) wireless communication networks will enable global coverage in space, air, ground, and sea. In this case, both base stations and users can be mobile and will tend to move continuously in three-dimensional (3D) space. Therefore, obtaining channel state information (CSI) in 3D continuous-space is crucial for the design and performance evaluation of future 6G and B6G wireless systems. On the other hand, new 6G technologies such as integrated sensing and communications (ISAC) will also require prior knowledge of CSI in 3D continuous-space. In this paper, a 3D continuous-space electromagnetic channel model is proposed for tri-polarized multi-user communications, taking into account scatterers and spherical wavefronts. Scattered fields are calculated using the method of moments (MoM) with high accuracy. Spherical wave functions are utilized to decompose the dyadic Green's functions that connect the transmitted source currents and the received electric fields. Simulation results demonstrate that transmit power, apertures, scatterers, and sample intervals have significant impacts on statistical properties and channel capacities, providing insights into the performance of continuous-space electromagnetic channel models and the design of future wireless systems. © 2025, CC BY.

关键词： Spheres

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Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices Induced by Random Interface Traps

Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices ...

引用

IEEE Conference on Nanotechnology

作者： Sekhar Reddy Kola Min-Hui Chuang Yiming Li Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering Institute of Communications Engineering Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Hsinchu Taiwan

Three-dimensional (3D) bulk fin-typed field effect transistors (FinFETs) have emerged as key devices that can scale down the technology node beyond 22-nm. However, the scaled devices have created new sources of fluctuation inherent in 3D geometry. The interface trap is one such fluctuation that is caused by the trapping and de-trapping of charge carriers and has an adverse effect on device characteristics and variability. In this work, we study impacts of random interface traps (RITs) on electrical characteristic of bulk FinFETs by using a 3D quantum-mechanically corrected device simulation. RIT position effects on short channel effects (SCEs) are examined with physical governed influence to show the major fluctuations. More than 50% reductions of the RITs-induced characteristic fluctuation of the germanium (Ge) devices are observed, compared with Si devices. The Ge ones can reduce SCE variations and exhibit high immunity to RITs.

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Thermo-mechanical characterization of insulating bio-plasters containing recycled volcanic pyroclasts

引用

Open Civil engineering Journal 2020年第1期14卷 66-77页

作者： Contrafatto, Loredana Gazzo, Salvatore Purrazzo, Antonio Gagliano, Antonio Department of Civil Engineering and Architecture University of Catania Catania Italy Material Testing Laboratory collaborator University of Catania Catania Italy Department of Electrical Electronics and Computer Engineering University of Catania Catania Italy

Aim: The research proposes the reuse of volcanic wastes in the production of lightened and insulating bio-plasters. Introduction: The goal is the production of a novel sustainable construction material that reduces the environmental impact. Methods: Four mixtures were designed. The recycled Volcanic Ash was used in combination with two bio-compatible binders;basically Natural Hydraulic Lime (NHL) or calcium hydroxide blended with a commercial Portland cement (CH-CEM). To improve thermal properties, CH-CEM mixtures were treated with an Air Entraining Agent (AEA) in two different percentages and a breathable resin (R). The main physical, mechanical and thermal properties were experimentally determined. Results: The results of such analysis indicate that the mixture NHL, realized using hydraulic lime as a binder, do not satisfy the threshold of the water absorption coefficient, exceeding the limit established by UNI EN 998-1 standard. Conclusion: On the contrary, one of the mixtures CH-CEM, containing both AEA and R, is suitable for use as lightweight plastering mortar and also satisfies the requirements for insulating mortars. © 2020 Contrafatto et al.

关键词： Bio-composite Bio-plasters Eco-design Etna Insulating panels Thermal insulating plaster Volcanic ash Volcanic pyroclsts

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Qubit-state purity oscillations from anisotropic transverse noise

引用

Physical Review A 2025年第3期111卷 032420-032420页

作者： David A. Rower Kotaro Hida Lamia Ateshian Helin Zhang Junyoung An Max Hays Sarah E. Muschinske Christopher M. McNally Samuel C. Alipour-Fard Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Applied Physics Graduate School of Engineering The University of Tokyo Bunkyo-ku Tokyo 113-8656 Japan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Center for Theoretical Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA The NSF AI Institute for Artificial Intelligence and Fundamental Interactions Cambridge Massachusetts 02139 USA

We explore the dynamics of qubit-state purity in the presence of transverse noise that is anisotropically distributed in the Bloch-sphere XY plane. We perform Ramsey experiments with noise injected along a fixed laboratory-frame axis and observe oscillations in the purity at twice the qubit frequency arising from the intrinsic qubit Larmor precession. We probe the oscillation dependence on the noise anisotropy, orientation, and power spectral density, using a low-frequency fluxonium qubit. Our results elucidate the impact of transverse noise anisotropy on qubit decoherence and may be useful for disentangling charge and flux noise in superconducting quantum circuits.

关键词： Qubits

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