Prospective evaluation of the diagnostic accuracy of FDG-PET/CT for the detection of sternal wound infection post-sternotomy by Angela Cai, Mehrshad Bakhshi, Yoan Lamarche, Francois Harel, Matthieu Pelletier-Galarneau

“…Positive and negative predictive values were 42% and 84%, respectively. The NPV was higher in the remote surgery group (100%) compared to the recent surgery group (73%). …”
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Diagnostic accuracy of drooling, reluctance, oropharynx, others, and leukocytosis score as a predictor of mortality and complications following acute corrosive ingestion by Fawaz Poonthottathil, Soorya Suresh, Jamshed Nayer, Praveen Aggarwal

“…The AUROC of DROOL score in predicting overall complications was 0.932 (95% CI: 0.877–0.987) and the AUROC of DROOL score in predicting mortality was 0.864 (95% CI: 0.758–0.970). …”
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Current status and development trends of deep coalbed methane research in China by Wei JU, Shu TAO, Zhaobiao YANG, Jiayao CHENG, Haiyan SHANG, Weike NING, Chunlong WU

“…Geological and engineering "dual sweet spot" prediction is a key research focus for deep CBM research. …”
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Comparison of Modified Biophysical Profile with Doppler Ultrasonographic Analysis in Determining Fetal well Being in the Third Trimester by Kadir Bakay, Ahmet Varolan, Ali Yazgan, Atif Akyol, İnci Davas

“…In conclusion, in order to effectively predict acute fetal distress and to maintain a reliable screening method, combined use of these tests, namely modified biophysical profile and umbilical artery Doppler analysis, has proven to be the most valuable and effective method as shown in our study. …”
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China’s CBM exploration and production and associated technological advancements: A review and reflections by Jianping YE

“…The geology-engineering integration serves as an effective method for the prediction and assessment of play fairways, well deployment, and the research and development of adaptive technologies. …”
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Automatic Segmentation of Abdominal Aortic Aneurysm From Computed Tomography Angiography Using a Patch-Based Dilated UNet Model by Merjulah Roby, Juan C. Restrepo, Haehwan Park, Satish C. Muluk, Mark K. Eskandari, Seungik Baek, Ender A. Finol

“…The framework adapted a fully developed patch-based dilated modified U-Net model, which shows remarkable efficiency in accurately delineating AAA regions within the CTA scans. During the prediction phase, the deep learning architecture demonstrates exceptional speed, requiring <inline-formula> <tex-math notation="LaTeX">$17~\pm ~0.02$ </tex-math></inline-formula> milliseconds per frame to generate the final segmented output. …”
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Use of machine learning in osteoarthritis research: a systematic literature review by Francis Berenbaum, Jérémie Sellam, David Klatzmann, Atul J Butte, Karine Louati, Encarnita Mariotti-Ferrandiz, Marie Binvignat, Valentina Pedoia

“…Twelve articles were related to diagnosis, 7 to prediction, 4 to phenotyping, 12 to severity and 11 to progression. …”
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Integrative analysis of 5-methylcytosine associated signature in papillary thyroid cancer by Ying Ding, Xinying Li, Wenlong Wang, Lei Cai

“…Similar to the above risk score, the IRS model also showed favorable prognosis predictive performance (AUC = 0.764). An integrated nomogram combining risk score, IRS, and age exhibited good prognostic predictive performance. …”
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Multiscale modeling of reservoir systems using geostatistical methods by Chihi, Hayet, Hammami, Mohamed Amin, Mezni, Imen, Belayouni, Habib, Ben Mammou, Abdallah

“…This provides a detailed input for the geostatistical modeling procedures that enabled to precisely capture the varying extent and shape of the hydrogeological units at regional scale.Geophysical data, available along the Jeffara plain, were added as a complement to the Jeffara geodatabase and used to establish the fault network and to build a local architectural model of the coastal aquifer system, based on time-to-depth conversion using kriging with external drift.The results have allowed (i) a major update of the geological configuration of the Jeffara basin, (ii) more precision on the geometries and extent of the stratigraphic sequences and (iii) an accurate prediction of the main characteristics of water reservoirs, i.e. their occurrence, thickness, facies and dynamic properties variation at the basin and reservoir scale. …”
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Social Acceptance of Smart Glasses in Health Care: Model Evaluation Study of Anticipated Adoption and Social Interaction by Niek Zuidhof, Oscar Peters, Peter-Paul Verbeek, Somaya Ben Allouch

“…In summary, constructs that focus on social interaction could contribute to better explanation and prediction of the expected adoption of smart glasses in health care. …”
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Associations of the Need for Surgery in Emergency Department Patients with Small Bowel Obstructions by Daniel J. Berman, Alexander W. Mahler, Ryan C. Burke, Andrew E. Bennett, Nathan I. Shapiro, Leslie A. Bilello

“…These associations are a step toward building better prediction models and improving decision-making in the ED, allowing for a more adequate treatment plan.…”
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Developing transcriptomic biomarkers for TAVO412 utilizing next generation sequencing analyses of preclinical tumor models by Ying Jin, Peng Chen, Huajun Zhou, Guangmao Mu, Simin Wu, Zhengxia Zha, Bin Ma, Chao Han, Mark L. Chiu, Mark L. Chiu

“…Together with specific driver mutation that associated with efficacy and the targets of TAVO412, a set of 21-gene biomarker was identified to predict the efficacy. A biomarker predictor was formulated based on the Linear Prediction Score (LPS) to estimate the probability of patients or tumor model response to TAVO412 treatment. …”
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Optimization of bioactive compounds and sensory quality in thermosonicated black carrot juice: A study using response surface methodology, gradient boosting, and fuzzy logic by Seydi Yıkmış, Melikenur Türkol, Ishak Pacal, Aylin Duman Altan, Nazlı Tokatlı, Gholamreza Abdi, Nazan Tokatlı Demirok, Rana Muhammad Aadil

“…RSM demonstrated higher prediction accuracy compared to GB, identifying optimal processing conditions at 48.68 °C, 11.15 minutes, and 82.62% amplitude. …”
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Increasing Safety of Vulnerable Road Users in Scenarios With Occlusion: A Collaborative Approach for Smart Infrastructures and Automated Vehicles by Thiago de Borba, Ondrej Vaculin, Hormoz Marzbani, Reza Nakhaie Jazar

“…The proposed extended perception system comprises four main modules: traffic monitoring, long-term motion prediction, collision risk assessment, and trajectory planning. …”
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Fuzzy Inference System Mamdani dalam Prediksi Produksi Kain Tenun Menggunakan Rule Berdasarkan Random Tree by Tundo Tundo, Shoffan Saifullah

“…When implemented in Fuzzy Mamdani, it can produce optimal woven fabric production predictions with predicted results less than the actual production. …”
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Deciphering the multifaceted mechanism of Shuang Huang Lian in treating upper respiratory tract infections: A metabolomics-based network pharmacology approach by Gang Xu, Akshay Suresh Patil, Ruhan Wei, Dan Liu, Aimin Zhou, Yan Xu

“…Key cheminformatics and bioinformatics platforms and databases, including ADMETlab, SEA, PASS, Super-Pred, SwissTargetPrediction, PharmMapper, and GeneCards, were used to predict the drug-like properties of active SHL components and identify protein targets shared between the active SHL components and the URTI-related disease genes. …”
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Konsep Decision Tree Reptree untuk Melakukan Optimasi Rule dalam Fuzzy Inference System Tsukamoto by Tundo Tundo, Shofwatul 'Uyun

“…Proof carried out in this research is one of them by using a comparison of decision trees J48 and Random Tree with the aim to find out the optimization of rules formed using the Tsukamoto system's fuzzy inference method, after calculating that the REPTree decision tree has a more average Forecasting Error Rate (AFER) error tree small of 23.17% with a truth value of 76.83%, while J48 has an error rate of 24.96%, with a truth value of 75.04%, while Random Tree has an error rate of 36.51%, with a truth value of 63, 49% in the case of prediction of palm oil production at PT Tapiana Nadenggan. …”
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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“…ResultsThe analysis of 23 included studies showcased the contributions of ML in identifying potential ablation targets, improving ablation strategies, and predicting patient prognosis. The patient data used in these studies comprised demographics, clinical characteristics, various types of imaging (9/23, 39%), and electrophysiological signals (7/23, 30%). …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

“…Additionally, we introduce a spatially-constrained loss function that mitigates gradient stability issues by considering the distance between label and prediction boundaries. We rigorously evaluated SSR-UNet on the ISIC2017 and ISIC2018 skin lesion segmentation benchmarks. …”
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Pendekatan Ensemble untuk Analisis Sentimen Covid19 Menggunakan Pengklasifikasi Soft Voting by Nova Agustina, Candra Nur Ihsan

“…The application of the ensemble method increases the accuracy of the model for sentiment prediction by up to 91%. …”
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