Significance of Chest Computed Tomography Scan Findings at Time of Diagnosis in Patients with COVID-19 Pneumonia by Rajaa Suhail Najim, Ahmed Diaa Abdulwahab, Dina Nasih Tawfeeq

“…The aim of this study was to summarize the significance of certain radiological features in evaluating Covid-19 pneumonia severity in Iraqi patients. …”
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Utilizing Machine Learning Techniques for Cancer Prediction and Classification based on Gene Expression Data by Mariwan Mahmood Hama Aziz, Sozan Abdullah Mahmood

“…It holds the promise of delivering systematic, precise, and scientifically backed diagnoses for different types of cancer. Lately, several studies have delved into cancer classification by leveraging data mining techniques, machine learning algorithms, and statistical methods to thoroughly analyze high-dimensional datasets. …”
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A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities, and Future Directions by Mahnoor, Imran Shafi, Mahnoor Chaudhry, Elizabeth Caro Montero, Eduardo Silva Alvarado, Isabel de la Torre Diez, Md Abdus Samad, Imran Ashraf

“…The paper includes a brief introduction to clustering, discussing various clustering algorithms, improvements in handling various data types, and appropriate evaluation metrics. …”
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Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…The predictive performance of models utilizing multispectral features, LiDAR-derived features, and a fusion of both modalities was evaluated against a benchmark model based on the Normalized Difference Vegetation Index (NDVI). …”
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Comparative Effectiveness of Early and Delayed Surgical Interventions in Patients with Acute Adhesive Intestinal Obstruction: A Multicenter Controlled Randomized Trial Prospective... by B. V. Sigua, A. E. Demko, S. V. Petrov, P. A. Kotkov, I. A. Soloviev, A. V. Vovk, A. V. Osipov, V. I. Serdyuk, D. A. Chernyshev, M. A. Protchenkov, I. I. Gubkov, M. G. Zaitsev, S. Yu. Puzanov, A. A. Kozobin, O. V. Babkov, A. V. Glebova, D. S. Sakhno, D. V. Gurzhiy, V. P. Zemlyanoy

“…During the implementation of the algorithm of actions, it was possible to achieve non-surgical resolution of AAIO phenomena in 86 patients (73.5%) of the main group, which, although statistically insignificant, exceeded the similar indicator of the comparison group, where successful conservative measures were carried out in 61 patients (61.6%) (χ2=3.48, p=0.06). …”
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A study on plant root apex morphology as a model for soft robots moving in soil. by Anand Kumar Mishra, Francesca Tramacere, Roberto Guarino, Nicola Maria Pugno, Barbara Mazzolai

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A novel model for predicting immunotherapy response and prognosis in NSCLC patients by Ting Zang, Xiaorong Luo, Yangyu Mo, Jietao Lin, Weiguo Lu, Zhiling Li, Yingchun Zhou, Shulin Chen

“…Methods Patients were randomly divided into training cohort and validation cohort at a ratio of 2:1. The random forest algorithm was applied to select important variables based on routine blood tests, and a random forest (RF) model was constructed to predict the efficacy and prognosis of ICIs treatment. …”
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A Practical Model for Predicting Esophageal Variceal Rebleeding in Patients with Hepatitis B-Associated Cirrhosis by Linxiang Liu, Yuan Nie, Qi Liu, Xuan Zhu

“…The objective of our study was to evaluate the ability of generating a extreme gradient boosting (XGBoost) algorithm model to improve the prediction of variceal rebleeding. …”
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Increasing comprehensiveness and reducing workload in a systematic review of complex interventions using automated machine learning by Olalekan A Uthman, Rachel Court, Jodie Enderby, Lena Al-Khudairy, Chidozie Nduka, Hema Mistry, GJ Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…The models were evaluated using recall, precision and work saved over sampling at no less than 95% recall. …”
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Revisiting the Role of Intravitreal Triamcinolone in Diabetic Macular Edema: 12-Month Outcomes after Bevacizumab Failure by Sukhum Silpa-archa, Variya Nganthavee, Peranut Chotcomwongse, Pawas Lalitwongsa, Paisan Ruamviboonsuk

“…Therefore, this study aimed to evaluate the treatment outcome of repeated intravitreal triamcinolone acetonide (IVTA) dosages for DME refractory to intravitreal bevacizumab over a 12-month period using a decision algorithm. …”
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Automated Analysis of Service Life of Air-Lines of the Electricity Transmission of Electric Power Systems by E. M. Farhadzadeh, A. Z. Muradaliyev, S. A. Abdullayeva, A. A. Nazarov

“…There are neither quantitative evaluations nor methodology for their performance. Therefore, a method and algorithm of quantitative assessment of integral indicators of reliability and safety of operation of thermal power units of thermal power plants as concentrated objects of continuous operation were previously analyzed by the authors. …”
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Rapid Classification and Quantitative Prediction of Aflatoxin B₁ Content and Colony Counts in Nutmeg Based on Electronic Nose by Ruiqi Yang, Keyao Zhu, Yuanyu Zhao, Xingyu Guo, Yushi Wang, Jiayu Wang, Huiqin Zou, Yonghong Yan

“…Subsequently, electronic nose (E-nose) was employed to analyze the odor of nutmeg and was combined with six machine learning algorithms to establish a classification model for samples with different degrees of mold. …”
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Sustainability index for eco-friendly cattle farming in dry climate regions by T. Simamora, M.N. Rofiq, L. Hutahaean, S. Sio, R. Hutapea, D. Irawan, Suryani ., R. Diastuti, U.N. Thiyas, B.A. Correia, L.T. Correia

“…The data that has been collected is analyzed employing Multidimensional Scaling and expedited appraisal software. To evaluate sustainability and leverage attributes, Monte Carlo analysis and the alternating least squares algorithm are applied.FINDINGS: The study's outcomes revealed that the sustainability index pertaining to beef cattle farming in dry climates recorded an average score of 53.09 percent. …”
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A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors by Rachele Rossanigo, Marco Caruso, Elena Dipalma, Cristine Agresta, Lucia Ventura, Franca Deriu, Andrea Manca, Taian M. Vieira, Valentina Camomilla, Andrea Cereatti

“…Segmentation of running data into gait cycles and stance/swing phases is crucial for evaluating running biomechanics. The benefit of magneto-inertial sensors is their ability to capture data in outdoor conditions. …”
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Detection of platelet-associated immunoglobulins and complement system components in patients with aplastic anemia and hemoblastosis by A. F. Rakhmani, E. A. Mikhaylova, I. V. Galtseva, Yu. O. Davidova, N. M. Kapranov, I. V. Dubinkin, S. M. Kulikov, T. V. Gaponova, Z. T. Fidarova, V. V. Troitskaya, E. N. Parovichnikova, V. G. Savchenko

“…Patients with AA were investigated on different stages of therapy and if refractoriness to donor's platelet transfusion is developed. …”
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DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network by Chunyu Dong, Jing Liu, Shenglong Xie

“…Moreover, there are occlusions and scale differences in the front and back rankings, which can easily cause confusion and interference with target features in the detection process, greatly limiting the accurate recognition ability of existing visual algorithms for classroom behavior. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…Additionally, it explores different advanced ML algorithms and their applications across various GDE types. …”
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Machine learning decision support model construction for craniotomy approach of pineal region tumors based on MRI images by Ziyan Chen, Yinhua Chen, Yandong Su, Nian Jiang, Siyi Wanggou, Xuejun Li

“…And also, 3 deep learning algorithms (ResNet-50, EfficientNetV2-m and ViT) were applied based on MRI images from different orientations. …”
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Identification of serum tRNA-derived small RNAs biosignature for diagnosis of tuberculosis by Zikun Huang, Qing Luo, Cuifen Xiong, Haiyan Zhu, Chao Yu, Jianqing Xu, Yiping Peng, Junming Li, Aiping Le

“…By utilizing cross-validation with a random forest algorithm approach, the training cohort achieved a sensitivity of 100% and specificity of 100%. …”
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Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study by Jayasai R. Rajagopal, Saikiran Rapaka, Faraz Farhadi, Ehsan Abadi, W. Paul Segars, Tristan Nowak, Puneet Sharma, William F. Pritchard, Ashkan Malayeri, Elizabeth C. Jones, Ehsan Samei, Pooyan Sahbaee

“…Abstract Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. …”
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