SLAS Technology最新文献

{"title":"ML-Driven Alzheimer’s disease prediction: A deep ensemble modeling approach","authors":"Mustafa Lateef Fadhil Jumaili ,&nbsp;Emrullah Sonuç","doi":"10.1016/j.slast.2025.100298","DOIUrl":"10.1016/j.slast.2025.100298","url":null,"abstract":"<div><div>Alzheimer’s disease (AD) is a progressive neurological disorder characterized by cognitive decline due to brain cell death, typically manifesting later in life.Early and accurate detection is critical for effective disease management and treatment. This study proposes an ensemble learning framework that combines five deep learning architectures (VGG16, VGG19, ResNet50, InceptionV3, and EfficientNetB7) to improve the accuracy of AD diagnosis. We use a comprehensive dataset of 3,714 MRI brain scans collected from specialized clinics in Iraq, categorized into three classes: NonDemented (834 images), MildDemented (1,824 images), and VeryDemented (1,056 images). The proposed voting ensemble model achieves a diagnostic accuracy of 99.32% on our dataset. The effectiveness of the model is further validated on two external datasets: OASIS (achieving 86.6% accuracy) and ADNI (achieving 99.5% accuracy), demonstrating competitive performance compared to existing approaches. Moreover, the proposed model exhibits high precision and recall across all stages of dementia, providing a reliable and robust tool for early AD detection. This study highlights the effectiveness of ensemble learning in AD diagnosis and shows promise for clinical applications.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100298"},"PeriodicalIF":2.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Postoperative self-care ability of continuous nursing based on artificial intelligence for stroke patients with neurological injury","authors":"Hui Zhao ,&nbsp;Na Li ,&nbsp;Jianmei Zhang","doi":"10.1016/j.slast.2025.100299","DOIUrl":"10.1016/j.slast.2025.100299","url":null,"abstract":"<div><div>According to the statistics of relevant data, stroke is a relatively common cerebrovascular disease, and its incidence rate is as high as 185/100,000 to 219/100,000. Continuous care can improve the quality of life of stroke patients and reduce the rate of hospital visits and hospitalizations. In this study, patients in a local hospital of third-grade class-A hospital were used as cases. Artificial intelligence was used to conduct continuous nursing intervention for the patients who were discharged from the stroke by using the WeChat platform, regular follow-up and home care. Afterwards, the collected data were given a post-processing, independent-samples <em>t</em>-test for two groups. After 3 months of extended care, the BI (Barthel Index) score of the intervention group has increased by 23.87 points, and the depression self-rating scale score has decreased by 9.12 points. Compared with the control group, the patients' self-care ability, depression state, compliance with health guidance and laboratory indicators were also better than those in the control group, and the differences were statistically significant (<em>P</em> &lt; 0.05). Compared with the control group, the trend of increasing the scores of each index was more significant in the intervention group.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100299"},"PeriodicalIF":2.5,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Scalable Deep Attention Mechanism of Instance Segmentation for the Investigation of Chromosome.","authors":"Neelam Umbreen, Sara Ali, Hasan Sajid, Yasar Ayaz, Shrooq Alsenan, Yunyoung Nam, So Yeon Kim, Muhammad Baber Sial","doi":"10.1016/j.slast.2025.100306","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100306","url":null,"abstract":"<p><p>Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and genomics due to the inherent complexity, variability in chromosome shapes, and the scarcity of high-quality annotated datasets. This study proposes a robust instance segmentation framework that integrates an automated annotation pipeline with an enhanced deep learning architecture to address these challenges. A novel dataset is introduced, comprising metaphase images and corresponding karyograms, annotated with precise instance segmentation information across 24 chromosome classes in COCO format. To overcome the labor-intensive manual annotation process, a feature-based image registration technique leveraging SIFT and homography is employed, enabling the accurate mapping of chromosomes from karyograms to metaphase images and significantly improving annotation quality and segmentation performance. The proposed framework includes a custom Mask R-CNN model enhanced with an Attention-based Feature Pyramid Network (AttFPN), spatial attention mechanisms, and a LastLevelMaxPool block for superior multi-scale feature extraction and focused attention on critical regions of the image. Experimental evaluations demonstrate the model's efficacy, achieving a mean average precision (mAP) of 0.579 at IoU = 0.50:0.95, surpassing the baseline Mask R-CNN and Mask R-CNN with AttFPN by 3.94% and 5.97% improvements in mAP and AP50, respectively. Notably, the proposed architecture excels in segmenting small and medium-sized chromosomes, addressing key limitations of existing methods. This research not only introduces a state-of-the-art segmentation framework but also provides a benchmark dataset, setting a new standard for chromosome instance segmentation in biomedical imaging. The integration of automated dataset creation with advanced model design offers a scalable and transferable solution, paving the way for tackling similar challenges in other domains of biomedical and cytogenetic imaging.</p>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100306"},"PeriodicalIF":2.5,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143999913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and optimization of a fluid flow splitting device for low-flow applications","authors":"Alexis K. Yates ,&nbsp;Heather N. Murray ,&nbsp;Ethan S. Lippmann","doi":"10.1016/j.slast.2025.100305","DOIUrl":"10.1016/j.slast.2025.100305","url":null,"abstract":"<div><div>Microfluidic devices are defined by the application of fluid flow to micron-scale features. Inherent to most experiments involving microfluidic devices is the need to precisely and reproducibly control fluid flow at the microliter scale, often through multiple inlet ports on a single device. While the number of fluid channels per device varies, perfusing multiple inputs requires either the use of multiple flow controllers (often syringe or peristaltic pumps) or the ability to evenly divide fluid across outlets. Towards the latter approach, while a handful of commercial systems exist for splitting fluid flow, these set-ups require significant financial investment, multiple flow control and sensing components, and restrict the user to a predetermined perfusion control system. Simple in-line splitting devices, such a manifolds or T junctions, fail to achieve flow splitting at low flow rates often used in microfluidic systems. To increase capabilities for flow-controlled experiments, we performed experimental analyses of the physical considerations governing even flow splitting under low flow, leading to the design of a microdevice (µ-Split) that can be directly inserted into existing microfluidic set-ups. The µ-Split allows for reproducible, even flow splitting from 10 uL/min to &gt; 2.5 mL/min. By testing multiple device geometries in combination with multiphysics simulations, we identified the design and fabrication features underlying the splitting precision achieved by the µ-Split. Overall, this work provides a useful tool to simplify microfluidic experiments that require evenly divided flow streams, while minimizing the overall device footprint.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100305"},"PeriodicalIF":2.5,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CirnetamorNet: An ultrasonic temperature measurement network for microwave hyperthermia based on deep learning","authors":"Fanbing Cui ,&nbsp;Yongxing Du ,&nbsp;Ling Qin ,&nbsp;Baoshan Li ,&nbsp;Chenlu Li ,&nbsp;Xianwei Meng","doi":"10.1016/j.slast.2025.100297","DOIUrl":"10.1016/j.slast.2025.100297","url":null,"abstract":"<div><h3>Objective</h3><div>Microwave thermotherapy is a promising approach for cancer treatment, but accurate noninvasive temperature monitoring remains challenging. This study aims to achieve accurate temperature prediction during microwave thermotherapy by efficiently integrating multi-feature data, thereby improving the accuracy and reliability of noninvasive thermometry techniques.</div></div><div><h3>Methods</h3><div>We proposed an enhanced recurrent neural network architecture, namely CirnetamorNet. The experimental data acquisition system is developed by using the material that simulates the characteristics of human tissue to construct the body model. Ultrasonic image data at different temperatures were collected, and 5 parameters with high temperature correlation were extracted from gray scale covariance matrix and Homodyned-K distribution. Using multi-feature data as input and temperature prediction as output, the CirnetamorNet model is constructed by multi-head attention mechanism. Model performance was evaluated by analyzing training losses, predicting mean square error and accuracy, and ablation experiments were performed to evaluate the contribution of each module.</div></div><div><h3>Results</h3><div>Compared with common models, the CirnetamorNet model performs well, with training losses as low as 1.4589 and mean square error of only 0.1856. Its temperature prediction accuracy of 0.3 °C exceeds that of many advanced models. Ablation experiments show that the removal of any key module of the model will lead to performance degradation, which proves that the collaboration of all modules is significant for improving the performance of the model.</div></div><div><h3>Conclusion</h3><div>The proposed CirnetamorNet model exhibits exceptional performance in noninvasive thermometry for microwave thermotherapy. It offers a novel approach to multi-feature data fusion in the medical field and holds significant practical application value.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100297"},"PeriodicalIF":2.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes of peripheral blood lymphocyte population in patients with head and neck squamous cell carcinoma undergoing concurrent chemotherapy","authors":"Guodong Man,&nbsp;Jianli Wang","doi":"10.1016/j.slast.2025.100303","DOIUrl":"10.1016/j.slast.2025.100303","url":null,"abstract":"<div><div>Although medical technology has improved the quality of life of HNSCC patients, their survival rate has not increased significantly, and their life and health continue to be threatened. With the help of modern medical technology, medical institutions can confirm the diagnosis of HNSCC patients in a timely manner, so as to take appropriate surgical treatment plans. However, surgery is difficult for patients with recurrent or metastatic HNSCC, and concurrent chemotherapy alone is not effective for HNSCC patients. Therefore, in this paper, the chemotherapy and immunotherapy of HNSCC patients were studied, and the following conclusions were drawn by detecting the peripheral blood lymphocytes of HNSCC patients. The NK cell (natural killer cell) index of healthy people was 6.64% higher than that of HNSCC patients. The CD4+/CD8+ ratio (CD4+ is inductive T cells and helper T cells, CD8+ is suppressor T cells and cytotoxic T cells) in HNSCC patients is in a downward trend during concurrent chemotherapy. Concurrent chemotherapy not only kills HNSCC cells, but also inhibits normal immune cells. The detection of peripheral blood lymphocytes of HNSCC patients has reference value for judging the immune function and curative effect of patients.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100303"},"PeriodicalIF":2.5,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143996424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contrast-enhanced ultrasonography combined with microbubbles for uterine disorders: Current trends and future perspectives","authors":"Jian Ding ,&nbsp;Wenhai Wang ,&nbsp;Wenbin Zhang ,&nbsp;Yinping Pan ,&nbsp;Dexin Xu","doi":"10.1016/j.slast.2025.100301","DOIUrl":"10.1016/j.slast.2025.100301","url":null,"abstract":"<div><div>Uterine disorders, including fibroids, polyps, and carcinomas, represent significant health concerns for women. Conventional diagnostic methods, including ultrasound and magnetic resonance imaging, often lack the sensitivity required to accurately delineate and evaluate these lesions. Consequently, there is a growing need for advanced imaging techniques to enhance both diagnostic precision and therapeutic decision-making. Standard imaging modalities typically provide low resolution, limiting their effectiveness in evaluating uterine pathology and determining optimal treatment strategies. In this context, microbubbles combined with contrast-enhanced ultrasonography offer a promising solution. This technique enhances the visualization of vascular patterns and tissue perfusion, facilitating a more accurate assessment of uterine lesions. Contrast-enhanced ultrasonography is less invasive, is more cost-effective, and offers real-time evaluation of vascular characteristics, making it a valuable tool for diagnosing uterine abnormalities. This review explores the clinical utility of contrast-enhanced ultrasonography with microbubbles in uterine diseases, focusing on its diagnostic accuracy, comparison with traditional imaging techniques, and its potential to improve the management of uterine pathology.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100301"},"PeriodicalIF":2.5,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alpha test 1 robotic platform for traditional Chinese medicine pretreatment: Automated modular integration and quality control applications","authors":"Lifei Gu ,&nbsp;Jiaxin Ma ,&nbsp;Lina Zeng ,&nbsp;Junyao Li ,&nbsp;Bing Wang ,&nbsp;Chang Su ,&nbsp;Shuhong Wang","doi":"10.1016/j.slast.2025.100300","DOIUrl":"10.1016/j.slast.2025.100300","url":null,"abstract":"<div><div>Sample pretreatment plays an important role in analytical performance, but it is often the rate-limiting step in scientific research. With the development of automation technology, automated sample preparation has become a powerful tool for liberating labor and improving efficiency. In this study, the automatic pretreatment of traditional Chinese medicine test was realized by module combination, and an intelligent robotic platform Alpha Test 1 was developed to decompose the complex preparation method of traditional Chinese medicine into automatic modular components. It includes a multi-channel liquid feeding device, an extraction bottle device, a reflux condensing pipe ring, a reflux extraction and a water bath extraction device. Each module is connected through modular combinations such as liquid injection control, intelligent sorting, and water bath condensation, and the difficulty of manual operation is gradually tackled to achieve the goal of replacing manual labor in the pretreatment process. We selected two representative traditional Chinese medicines, Xianglian Pills and Erzhi Pills, to explore their application in the testing of traditional Chinese medicine. The results of Alpha Test 1 in the identification and content determination met the requirements of Chinese Pharmacopoeia, and the operation was simple, rapid and efficient compared with the manual pretreatment method. This method can meet the requirements of daily laboratory testing and provide technical support for the quality control evaluation and testing of traditional Chinese medicine.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100300"},"PeriodicalIF":2.5,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Efficacy of Invasive Mechanical Ventilation in ICU Patients with Severe Heart Failure","authors":"Darina Bao ,&nbsp;Xin Wang ,&nbsp;Chen Zhou ,&nbsp;Xiaofei Liu ,&nbsp;Yanmei Liu","doi":"10.1016/j.slast.2025.100302","DOIUrl":"10.1016/j.slast.2025.100302","url":null,"abstract":"<div><div>In order to study the clinical treatment effect and analyze the main clinical effects of invasive mechanical ventilation in ICU patients with severe heart failure, this paper proposes a efficacy analysis method based on invasive mechanical ventilation for ICU patients with severe heart failure. This study used a retrospective analysis to select 50 patients with severe heart failure admitted to the ICU of a certain hospital from January 2021 to March 2022 as the research subjects, divided into a control group and an observation group. The control group received conventional treatment methods, while the observation group received invasive mechanical ventilation treatment in addition to conventional treatment, and a nursing quality index system was constructed to verify the feasibility and scientificity of the treatment plan. The research results showed that the treatment effectiveness rate of the observation group was 96%, significantly higher than the control group's 84%. In addition, the arterial oxygen saturation (SaO ₂) and partial pressure of oxygen (PaO ₂) in the observation group were significantly increased after treatment compared to the control group, while the partial pressure of carbon dioxide (PaCO ₂) was lower (P&lt;0.05). In addition, in order to improve the comprehensiveness of the analysis, this study further explored the epidemiological characteristics of patients with severe heart failure, including the influence of age, complications (such as diabetes, hypertension, etc.), course characteristics and other factors on the treatment effect. At the same time, an in-depth analysis was conducted on the application strategies of invasive mechanical ventilation in the treatment of severe heart failure, including airway management, ventilator mode optimization, complication prevention, and nursing measures. In addition, this study compared the applicability of invasive and non-invasive mechanical ventilation in the treatment of severe heart failure patients and evaluated the impact of different mechanical ventilation strategies on patient prognosis. To sum up, this study shows that invasive mechanical ventilation can significantly improve the treatment effect of patients with severe heart failure in ICU, improve the oxygenation level and reduce carbon dioxide retention, while optimizing the quality of care and improving the survival rate. The conclusion of this study provides a reference for clinical practice and proposes exploration directions for further optimizing mechanical ventilation strategies in the future.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"32 ","pages":"Article 100302"},"PeriodicalIF":2.5,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for the special issue: \"Natural language processing and large language models in life sciences\".","authors":"Akshi Kumar, Mps Bhatia","doi":"10.1016/j.slast.2025.100296","DOIUrl":"https://doi.org/10.1016/j.slast.2025.100296","url":null,"abstract":"","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":" ","pages":"100296"},"PeriodicalIF":2.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}