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Journals Computer Methods and Programs ...

Computer Methods and Programs in Biomedicine

https://read.qxmd.com/read/38537494/disease-x-epidemic-control-using-a-stochastic-model-and-a-deterministic-approximation-performance-comparison-with-and-without-parameter-uncertainties
#1
JOURNAL ARTICLE
Julien Flaig, Nicolas Houy
BACKGROUND: The spread of infectious diseases can be modeled using deterministic or stochastic models. A deterministic approximation of a stochastic model can be appropriate under some conditions, but is unable to capture the discrete nature of populations. We look into the choice of a model from the perspective of decision making. METHOD: We consider an emerging disease (Disease X) in a closed population modeled by a stochastic SIR model or its deterministic approximation...
March 20, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38522371/agent-based-systems-in-healthcare
#2
EDITORIAL
Sara Montagna, Stefano Mariani, Michael I Schumacher, Gaetano Manzo
This Special Issue is dedicated to discussing which are the advantages, challenges and open issues in the application of the agent-based approach as a part of the digital transformation in the healthcare sector. Agent-based technology in healthcare optimises resource allocation and coordination and supports clinical decision-making. Challenges, such as model reliability and interdisciplinary collaboration, must be addressed for widespread adoption. Embracing this technology promises improved healthcare delivery and better patient outcomes...
March 19, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38522329/patient-specific-left-atrium-contraction-quantification-associated-with-atrial-fibrillation-a-region-based-approach
#3
JOURNAL ARTICLE
Sachal Hussain, Matteo Falanga, Antonio Chiaravalloti, Corrado Tomasi, Cristiana Corsi
BACKGROUND AND OBJECTIVES: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that significantly impacts heart function. AF disrupts atrial mechanical contraction, leading to irregular, uncoordinated, and slow blood flow inside the atria which favors the formation of clots, primarily within the left atrium (LA). A standardized region-based analysis of the LA is missing, and there is not even any consensus about how to define the LA regions. In this study we propose an automatic approach for regionalizing the LA into segments to provide a comprehensive 3D region-based LA contraction assessment...
March 19, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38520784/cphamas-an-online-platform-for-pharmacokinetic-data-analysis-based-on-optimized-parameter-fitting-algorithm
#4
JOURNAL ARTICLE
Yun Kuang, Dong-Sheng Cao, Yong-Hui Zuo, Jing-Han Yuan, Feng Lu, Yi Zou, Hong Wang, Dan Jiang, Qi Pei, Guo-Ping Yang
BACKGROUND AND OBJECTIVE: Clinical pharmacological modeling and statistical analysis software is an essential basic tool for drug development and personalized drug therapy. The learning curve of current basic tools is steep and unfriendly to beginners. The curve is even more challenging in cases of significant individual differences or measurement errors in data, resulting in difficulties in accurately estimating pharmacokinetic parameters by existing fitting algorithms. Hence, this study aims to explore a new optimized parameter fitting algorithm that reduces the sensitivity of the model to initial values and integrate it into the CPhaMAS platform, a user-friendly online application for pharmacokinetic data analysis...
March 19, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38507960/a-novel-feature-level-fusion-scheme-with-multimodal-attention-cnn-for-heart-sound-classification
#5
JOURNAL ARTICLE
Kalpeshkumar Ranipa, Wei-Ping Zhu, M N S Swamy
BACKGROUND AND OBJECTIVE: Most of the existing machine learning-based heart sound classification methods achieve limited accuracy. Since they primarily depend on single domain feature information and tend to focus equally on each part of the signal rather than employing a selective attention mechanism. In addition, they fail to exploit convolutional neural network (CNN) - based features with an effective fusion strategy. METHODS: In order to overcome these limitations, a novel multimodal attention convolutional neural network (MACNN) with a feature-level fusion strategy, in which Mel-cepstral domain as well as general frequency domain features are incorporated to increase the diversity of the features, is proposed in this paper...
March 15, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38520785/sc-net-symmetrical-conical-network-for-colorectal-pathology-image-segmentation
#6
JOURNAL ARTICLE
Gang Zhang, Zifen He, Yinhui Zhang, Zhenhui Li, Lin Wu
BACKGROUND AND OBJECTIVE: Image segmentation of histopathology of colorectal cancer is a core task of computer aided medical image diagnosis system. Existing convolutional neural networks generally extract multi-scale information in linear flow structures by inserting multi-branch modules, which is difficult to extract heterogeneous semantic information under multi-level and different receptive field and tough to establish context dependency among different receptive field features. METHODS: To address these issues, we propose a symmetric spiral progressive feature fusion encoder-decoder network called the Symmetric Conical Network (SC-Net)...
March 13, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38503070/breaking-presence-in-immersive-virtual-reality-toward-behavioral-and-emotional-engagement
#7
JOURNAL ARTICLE
Oscar I Caldas, Mauricio Mauledoux, Oscar F Aviles, Carlos Rodriguez-Guerrero
BACKGROUND AND OBJECTIVE: Many recent studies in virtual reality (VR) have managed the sense of Presence to assess the suitability of their designs, mainly when focused on learning goals that require high user engagement, such as in serious games for psychomotor training. However, the place and plausibility illusions needed to promote Presence are achieved by combining different VR-based design cues, and their individual contribution to preserving the Presence's engagement/involvement component is still unclear...
March 13, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38492277/estimation-of-the-in-plane-ultimate-stress-of-lamellar-tissue-as-a-function-of-bone-mineral-density-and-osteocyte-lacunae-porosity
#8
JOURNAL ARTICLE
Ana Vercher-Martínez, Raquel Megías, Ricardo Belda, Pablo Vargas, Eugenio Giner
BACKGROUND AND OBJECTIVE: Detailed finite element models based on medical images (μ-CT) are commonly used to analyze the mechanical behavior of bone at microscale. In order to simulate the tissue failure onset, isotropic failure criteria of lamellar tissue are often used, despite its non-isotropic and heterogeneous nature. The main goal of the present work is to estimate the in-plane ultimate stress of lamellar bone, considering the influence of mineral content and the porosity due to the osteocyte lacunae concentration...
March 13, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38489935/reliable-prediction-of-difficult-airway-for-tracheal-intubation-from-patient-preoperative-photographs-by-machine-learning-methods
#9
JOURNAL ARTICLE
Fernando García-García, Dae-Jin Lee, Francisco J Mendoza-Garcés, Susana García-Gutiérrez
BACKGROUND: Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity. OBJECTIVE: To develop and evaluate machine learning (ML) and deep learning (DL) algorithms for the reliable prediction of intubation risk, using information about airway morphology. METHODS: Observational, prospective cohort study enrolling n=623 patients who underwent tracheal intubation: 53/623 difficult cases (prevalence 8...
March 12, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38503071/sensitivity-analysis-of-paediatric-knee-kinematics-to-the-graft-surgical-parameters-during-anterior-cruciate-ligament-reconstruction-a-sequentially-linked-neuromusculoskeletal-finite-element-analysis
#10
JOURNAL ARTICLE
Ayda Karimi Dastgerdi, Amir Esrafilian, Christopher P Carty, Azadeh Nasseri, Martina Barzan, Rami K Korhonen, Ivan Astori, Wayne Hall, David John Saxby
BACKGROUND AND OBJECTIVE: Incidence of paediatric anterior cruciate ligament (ACL) rupture has increased substantially over recent decades. Following ACL rupture, ACL reconstruction (ACLR) surgery is typically performed to restore passive knee stability. This surgery involves replacing the failed ACL with a graft, however, surgeons must select from range of surgical parameters (e.g., type, size, insertion, and pre-tension) with no robust evidence guiding these decisions. This study presents a systemmatic computational approach to study effects of surgical parameter variation on kinematics of paediatric knees...
March 11, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38531147/mob-cbam-a-dual-channel-attention-based-deep-learning-generalizable-model-for-breast-cancer-molecular-subtypes-prediction-using-mammograms
#11
JOURNAL ARTICLE
Iqra Nissar, Shahzad Alam, Sarfaraz Masood, Mohammad Kashif
BACKGROUND AND OBJECTIVE: Deep Learning models have emerged as a significant tool in generating efficient solutions for complex problems including cancer detection, as they can analyze large amounts of data with high efficiency and performance. Recent medical studies highlight the significance of molecular subtype detection in breast cancer, aiding the development of personalized treatment plans as different subtypes of cancer respond better to different therapies. METHODS: In this work, we propose a novel lightweight dual-channel attention-based deep learning model MOB-CBAM that utilizes the backbone of MobileNet-V3 architecture with a Convolutional Block Attention Module to make highly accurate and precise predictions about breast cancer...
March 10, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38479148/iodeep-an-iod-for-the-introduction-of-deep-learning-in-the-dicom-standard
#12
JOURNAL ARTICLE
Salvatore Contino, Luca Cruciata, Orazio Gambino, Roberto Pirrone
BACKGROUND AND OBJECTIVE: In recent years, Artificial Intelligence (AI) and in particular Deep Neural Networks (DNN) became a relevant research topic in biomedical image segmentation due to the availability of more and more data sets along with the establishment of well known competitions. Despite the popularity of DNN based segmentation on the research side, these techniques are almost unused in the daily clinical practice even if they could support effectively the physician during the diagnostic process...
March 8, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38471292/stcgru-a-hybrid-model-based-on-cnn-and-bigru-for-mild-cognitive-impairment-diagnosis
#13
JOURNAL ARTICLE
Hao Zhou, Liyong Yin, Rui Su, Ying Zhang, Yi Yuan, Ping Xie, Xin Li
BACKGROUND AND OBJECTIVE: Early diagnosis of mild cognitive impairment (MCI) is one of the essential measures to prevent its further development into Alzheimer's disease (AD). In this paper, we propose a hybrid deep learning model for early diagnosis of MCI, called spatio-temporal convolutional gated recurrent unit network (STCGRU). METHODS: The STCGRU comprises three bespoke convolutional neural network (CNN) modules and a bi-directional gated recurrent unit (BiGRU) module, which can effectively extract the spatial and temporal features of EEG and obtain excellent diagnostic results...
March 8, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38460346/tipdet-a-multi-keyframe-motion-aware-framework-for-tip-detection-during-ultrasound-guided-interventions
#14
JOURNAL ARTICLE
Ruixin Wang, Guoping Tan, Xiaohui Liu
BACKGROUND AND OBJECTIVE: Automatic needle tip detection is important in real-time ultrasound (US) images that are utilized to guide interventional needle puncture procedures in clinical settings. However, due to the spatial indiscernibility problem caused by the severe background interferences and the tip characteristics of small size, being grayscale and indistinctive appearance patterns, tip detection in US images is challenging. METHODS: To achieve precise tip detection in US images against spatial indiscernibility, a novel multi-keyframe motion-aware framework called TipDet is proposed...
March 8, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38503072/brain-mr-image-simulation-for-deep-learning-based-medical-image-analysis-networks
#15
JOURNAL ARTICLE
Aymen Ayaz, Yasmina Al Khalil, Sina Amirrajab, Cristian Lorenz, Jürgen Weese, Josien Pluim, Marcel Breeuwer
BACKGROUND AND OBJECTIVE: As large sets of annotated MRI data are needed for training and validating deep learning based medical image analysis algorithms, the lack of sufficient annotated data is a critical problem. A possible solution is the generation of artificial data by means of physics-based simulations. Existing brain simulation data is limited in terms of anatomical models, tissue classes, fixed tissue characteristics, MR sequences and overall realism. METHODS: We propose a realistic simulation framework by incorporating patient-specific phantoms and Bloch equations-based analytical solutions for fast and accurate MRI simulations...
March 7, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38479147/active-learning-for-left-ventricle-segmentation-in-echocardiography
#16
JOURNAL ARTICLE
Eman Alajrami, Tiffany Ng, Jevgeni Jevsikov, Preshen Naidoo, Patricia Fernandes, Neda Azarmehr, Fateme Dinmohammadi, Matthew J Shun-Shin, Nasim Dadashi Serej, Darrel P Francis, Massoud Zolgharni
BACKGROUND AND OBJECTIVE: Training deep learning models for medical image segmentation require large annotated datasets, which can be expensive and time-consuming to create. Active learning is a promising approach to reduce this burden by strategically selecting the most informative samples for segmentation. This study investigates the use of active learning for efficient left ventricle segmentation in echocardiography with sparse expert annotations. METHODS: We adapt and evaluate various sampling techniques, demonstrating their effectiveness in judiciously selecting samples for segmentation...
March 7, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38479146/dax-net-a-dual-branch-dual-task-adaptive-cross-weight-feature-fusion-network-for-robust-multi-class-cancer-classification-in-pathology-images
#17
JOURNAL ARTICLE
Doanh C Bui, Boram Song, Kyungeun Kim, Jin Tae Kwak
BACKGROUND AND OBJECTIVE: Multi-class cancer classification has been extensively studied in digital and computational pathology due to its importance in clinical decision-making. Numerous computational tools have been proposed for various types of cancer classification. Many of them are built based on convolutional neural networks. Recently, Transformer-style networks have shown to be effective for cancer classification. Herein, we present a hybrid design that leverages both convolutional neural networks and transformer architecture to obtain superior performance in cancer classification...
March 7, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38461712/facial-augmented-reality-based-on-hierarchical-optimization-of-similarity-aspect-graph
#18
JOURNAL ARTICLE
Long Shao, Tianyu Fu, Yucong Lin, Deqiang Xiao, Danni Ai, Tao Zhang, Jingfan Fan, Hong Song, Jian Yang
BACKGROUND: The existing face matching method requires a point cloud to be drawn on the real face for registration, which results in low registration accuracy due to the irregular deformation of the patient's skin that makes the point cloud have many outlier points. METHODS: This work proposes a non-contact pose estimation method based on similarity aspect graph hierarchical optimization. The proposed method constructs a distance-weighted and triangular-constrained similarity measure to describe the similarity between views by automatically identifying the 2D and 3D feature points of the face...
March 7, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38484409/circadian-assessment-of-heart-failure-using-explainable-deep-learning-and-novel-multi-parameter-polar-images
#19
JOURNAL ARTICLE
Mohanad Alkhodari, Ahsan H Khandoker, Herbert F Jelinek, Angelos Karlas, Stergios Soulaidopoulos, Petros Arsenos, Ioannis Doundoulakis, Konstantinos A Gatzoulis, Konstantinos Tsioufis, Leontios J Hadjileontiadis
BACKGROUND AND OBJECTIVE: Heart failure (HF) is a multi-faceted and life-threatening syndrome that affects more than 64.3 million people worldwide. Current gold-standard screening technique, echocardiography, neglects cardiovascular information regulated by the circadian rhythm and does not incorporate knowledge from patient profiles. In this study, we propose a novel multi-parameter approach to assess heart failure using heart rate variability (HRV) and patient clinical information. METHODS: In this approach, features from 24-hour HRV and clinical information were combined as a single polar image and fed to a 2D deep learning model to infer the HF condition...
March 6, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38484410/tdasd-generating-medically-significant-fine-grained-lung-adenocarcinoma-nodule-ct-images-based-on-stable-diffusion-models-with-limited-sample-size
#20
JOURNAL ARTICLE
Yidan Xu, Jiaqing Liang, Yaoyao Zhuo, Lei Liu, Yanghua Xiao, Lingxiao Zhou
BACKGROUND AND OBJECTIVES: Spread through air spaces (STAS) is an emerging lung cancer infiltration pattern. Predicting its spread through CT scans is crucial. However, limited STAS data makes this prediction task highly challenging. Stable diffusion is capable of generating more diverse and higher-quality images compared to traditional GAN models, surpassing the dominating GAN family models in image synthesis over the past few years. To alleviate the issue of limited STAS data, we propose a method TDASD based on stable diffusion, which is able to generate high-resolution CT images of pulmonary nodules corresponding to specific nodular signs according to the medical professionals...
March 5, 2024: Computer Methods and Programs in Biomedicine
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