Article
Biology
Qing Xu, Wenting Duan
Summary: In this paper, a dual attention supervised module, named DualAttNet, is proposed for multi-label lesion detection in chest radiographs. By efficiently fusing global and local lesion classification information, the module is able to recognize targets with different sizes. Experimental results show that DualAttNet outperforms baselines in terms of mAP and AP50 with different detection architectures.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Juan Antonio Valera-Calero, Dario Lopez-Zanoni, Sandra Sanchez-Jorge, Cesar Fernandez-de-las-Penas, Marcos Jose Navarro-Santana, Sofia Olivia Calvo-Moreno, Gustavo Plaza-Manzano
Summary: This study developed an easy-to-use application for assessing the diagnostic accuracy of digital pain drawings (PDs) compared to the classic paper-and-pencil method. The results demonstrated that digital PDs have higher reliability and accuracy compared to paper-and-pencil PDs, and there were no significant differences in assessing pain extent between the two methods. The PAIN EXTENT app showed good convergent validity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes
Summary: This study introduces a novel hybrid model called ConTraNet, which combines the strengths of CNN and Transformer neural networks, and achieves significant improvement in classification performance with limited training data.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jun Cao, Lichao Yang, Ptolemaios Georgios Sarrigiannis, Daniel Blackburn, Yifan Zhao
Summary: Alzheimer's disease and Parkinson's disease are common neurodegenerative diseases. Effective brain connectivity has the potential for disease diagnosis. This study proposes a novel directed structure learning GNN model that combines brain connectivity estimations and graph neural network techniques for dementia diagnosis, achieving promising results.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Alireza Rafiei, Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran
Summary: This study aimed to improve machine learning model prediction of fluid overload by integrating synthetic data, which could be translated to other clinical outcomes.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Siwei Tao, Zonghan Tian, Ling Bai, Yueshu Xu, Cuifang Kuang, Xu Liu
Summary: This study proposes a transfer learning-based method to address the phase retrieval problem in grating-based X-ray phase contrast imaging. By generating a training dataset and using deep learning techniques, this method improves image quality and can be applied to X-ray 2D and 3D imaging.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Akshata K. Naik, Venkatanareshbabu Kuppili
Summary: Gene selection is crucial for classifying high-dimensional microarray gene expression data. This paper proposes a neural network-based embedded feature selection method called Weighted GCNN (WGCNN), which can capture non-linear interactions and solve multi-class problems. The WGCNN incorporates feature weighting and statistical guided dropout to avoid overfitting. Experimental validation demonstrates that the WGCNN performs well in terms of F1 score and number of features selected.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hongliang Guo, Hanbo Liu, Ahong Zhu, Mingyang Li, Helong Yu, Yun Zhu, Xiaoxiao Chen, Yujia Xu, Lianxing Gao, Qiongying Zhang, Yangping Shentu
Summary: In this paper, a BDSMA-based image segmentation method is proposed, which improves the limitations of the original algorithm by combining SMA with DE and introducing a cooperative mixing model. The experimental results demonstrate the superiority of this method in terms of convergence speed and precision compared to other methods, and its successful application to brain tumor medical images.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Abir U. Igamberdiev
Summary: Biological systems strive to maximize self-maintenance and adaptability by establishing stable non-equilibrium states that organize the fluxes of matter and energy and control metabolic processes. These states are realized in autopoietic structures that operate based on biological codes. The principle of thermodynamic buffering optimizes metabolic fluxes, and in developing systems, the principle transforms into increasing external work. Bauer's concept of the stable non-equilibrium state places thermodynamics within the framework of internal biological causality, providing a relational theory of biological thermodynamics.
Article
Biology
Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Heejung Choi, Ha Na Cho, Minkyoung Kim, Jiye Han, Gaeun Kee, Seohyun Park, Kye Hwa Lee, Tae Joon Jun, Young-Hak Kim
Summary: Electronic medical records have potential in advancing healthcare technologies, but privacy issues hinder their full utilization. Deep learning-based generative models can mitigate this problem by creating synthetic data similar to real patient data. However, the risk of data leakage due to malicious attacks poses a challenge to traditional generative models. To address this, we propose a method that employs local differential privacy (LDP) to protect the model from attacks and preserve the privacy of training data, while generating medical data with reasonable performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Shuai Liu, Shuo Chen, Lanlan Xiao, Kaixuan Zhang, Yuan Qi, Hao Li, Yuan Cheng, Zixin Hu, Chensen Lin
Summary: This paper presents a mesoscopic cell-level numerical model based on dissipative particle dynamics to capture the complex interaction between deformable cells and flow within the DLD device. The model's credibility is established through numerical simulations and validation with experimental data. The study also extends the existing theory for predicting the zigzag mode in solid spherical particles to encompass the behavior of red blood cells, introducing a new concept of effective diameter that provides highly accurate predictions.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Wei-luo Cai, Mo Cheng, Yi Wang, Pei-hang Xu, Xi Yang, Zheng-wang Sun, Wang-jun Yan
Summary: Cancer metastasis is a major cause of cancer progression and treatment difficulty. This study identified genes associated with different tissue metastases and proposed a CNN-based model, MDCNN, for predicting metastasis occurrence. The model achieved satisfactory prediction accuracy and outperformed other methods. Further analysis revealed pathways and immune infiltration associated with bone metastasis.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hossein Sharifi, Lik Chuan Lee, Kenneth S. Campbell, Jonathan F. Wenk
Summary: In this study, a new multiscale model of the cardiovascular system named MyoFE is presented. The model integrates a mechanistic model of contraction at the myosin level into a finite element-based model of the left ventricle pumping blood through the systemic circulation. The model is coupled with a closed-loop feedback control of arterial pressure inspired by a baroreflex algorithm, showing the ability to maintain arterial pressure in different conditions.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biodiversity Conservation
Petrus C. J. Grobler, Angus Macgregor Myburgh, Aaron Barnes, Savel R. R. Daniels
Summary: This study examined the species boundaries of the velvet worm Peripatopsis birgeri species complex in South Africa using DNA sequence data, morphology, SEM and ecological niche modelling. Two geographically distinct clades were found within the species complex. The results of species delimitation methods were incongruent and overestimated the number of species. Niche modelling revealed differences in habitat preferences between the two clades. Gross morphological characteristics did not differ between the clades, but SEM revealed fixed differences in scale arrangement. A new species, P. polychroma, was described from the northern Drakensberg.
SYSTEMATICS AND BIODIVERSITY
(2023)
Article
Biodiversity Conservation
R. Virgili, A. Poliseno, T. Fujita, G. A. Pratama, I. Fernandez-Silva, J. D. Reimer
Summary: This study used an integrated approach to clarify the taxonomic placement of the genus Dorometra within family Antedonidae. The results showed that Dorometra is polyphyletic and its species are divided into three main clades spread within other Antedonidae. The study also revealed cryptic diversity within the species Dorometra nana.
SYSTEMATICS AND BIODIVERSITY
(2023)
Book Review
Biodiversity Conservation
Andrew V. Z. Brower
SYSTEMATICS AND BIODIVERSITY
(2023)
Article
Biodiversity Conservation
Maria S. Vorontsova, Kurt B. Petersen, Patrick Minx, Taylor M. Aubuchon-Elder, M. Cinta Romay, Edward S. Buckler, Elizabeth A. Kellogg
Summary: The genus Andropogon sensu lato is polyphyletic. This study adjusts its classification and reestablishes the genus Anatherum. Plastome phylogeny and morphological diversity were assessed to understand the evolutionary history and distinguishing features of Andropogon sensu lato.
SYSTEMATICS AND BIODIVERSITY
(2023)
Article
Biodiversity Conservation
Dmitry M. Atopkin, Yana I. Ivashko, Vladimir V. Besprozvannykh, Alexandr E. Zhokhov
Summary: New morphological and molecular data on Lissorchiidae trematodes from fish in the Russian Far East were generated. Four new species were established based on molecular data and morphological characteristics. The study confirmed the previous classification results of Lissorchiidae and provided the first molecular data on Asymphylotrema macrocetabulum.
SYSTEMATICS AND BIODIVERSITY
(2023)
Article
Biodiversity Conservation
Giulia Perina, Ana I. Camacho, Melissa Danks, Nicole White, Michelle T. Guzik
Summary: Fifteen species of the Gondwanan genus Atopobathynella from four countries have been described. The position of the genus within the family and its species relationships are controversial. The arid zones of Western Australia have been recognized as a hotspot for subterranean fauna, and sampling was conducted in the Pilbara region. Two new species, Atopobathynella yarriensis sp. nov. and A. degreyensis sp. nov., were described and supported by molecular and morphological data.
SYSTEMATICS AND BIODIVERSITY
(2023)
Article
Biodiversity Conservation
Leonardo De Oliveira, Felipe Gobbi Grazziotin, Paola Maria Sanchez-Martinez, Mahmood Sasa, Oscar Flores-Villela, Ana Lucia Da Costa Prudente, Hussam Zaher
Summary: A new study reveals that goo-eating snakes have a unique venom delivery system that relies on their lower jaw instead of upper lip and maxillary glands. This change likely occurred in the ancestor of goo-eating snakes, possibly due to the loss of the embryonic posterior maxillary lamina.
SYSTEMATICS AND BIODIVERSITY
(2023)
