Comparative Analysis of Random Forest and Logistic Regression Methods in Predicting Leukemia Blood Cancer Using Microscopic Blood Cell Images by Jepri Banjarnahor, Galuh Wira Relungwangi

“…These findings suggest that ensemble methods like RF are particularly well-suited for detecting one of the most deadly blood cancers, leukemia, due to their ability to handle complex feature interactions in medical imaging data. …”
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Automated Segmentation of Acute Ischemic Stroke Using Attention U-net with Patch Mechanism by CINAR, N., UCAN, M., KAYA, B., KAYA, M.

“…The study aims to develop a model for automatic segmentation of ischemic stroke areas, facilitating efficient diagnosis in medical settings. An enhanced Attention U-Net model with a patch-based approach using MRI data is proposed for this purpose. …”
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Type 2 diabetes: Primary prevention, screening and health care approach for diagnosis in South Africa by Pankaj Joshi, Shaifali Joshi

“…These periods can be from 8–10 years as extrapolated from the United Kingdom Prospective Diabetes Study data. This phase of pre-diabetes is not innocuous, and is often associated with the concurrent development of complications, which highlights the importance of early detection and treatment of this ‘silent killer’. …”
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Developing a Non-Invasive Intelligent System for Blood Glucose Level Estimation Using Reflective Optical Sensors by Mihaela MARIN, Teodora Alexandra DOBRIN, Florin Bogdan MARIN

“…The system integrates a detection unit equipped with an infrared LED, phototransistor, microcontroller, OLED display, and Bluetooth module-with realtime data visualization and wireless transmission to mobile devices. …”
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Wearable devices for patient monitoring in the intensive care unit by Alessandra Angelucci, Massimiliano Greco, Maurizio Cecconi, Andrea Aliverti

“…WDs are also promising tools in applications like delirium detection, vital signs monitoring in limited resource settings, and prevention of hospital-acquired pressure injuries. …”
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On the Effectiveness of Automatic Code Generation for Synthetic Dataset Creation by Josh Mitchell, Varghese Mathew Vaidyan, Yong Wang

“…Our findings have important implications for vulnerability detection and malware analysis systems, and the research shows that synthetic data generation can effectively complement or potentially surpass real-world samples. …”
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Current trends in neurocritical care: a comprehensive review by Vinothini Murugaiyan, Kingston Samraj Kirubakaran Jebaraj, Srinivas Kalaiselvan

“…Continuous neuromonitoring using tools like electroencephalogram and intracranial pressure monitoring offers real-time data on brain function, aiding in the early detection of complications. …”
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Dealing with adverse drug reactions in the context of polypharmacy using regression models by Jakob Sommer, Roberto Viviani, Justyna Wozniak, Julia C. Stingl, Katja S. Just

“…While these regressions generate valuable information, there are still challenges in setting appropriate thresholds for determining and interpreting the positive results.…”
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Decoding Consumer Sentiments: Advanced NLP Techniques for Analyzing Smartphone Reviews by Shaista Jabeen

“…Conclusions: the application of BERT and sentence transformers provides a significant technological advancement in the field of text analysis by enhancing the granularity of sentiment detection and offering a robust framework for interpreting complex data sets. …”
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The variety of abomasal nematode communities of captive and free-roaming populations of European bison, Bison bonasus (L.): a morphometric and molecular approach by Marta Gałązka, Katarzyna Filip-Hutsch, Daniel Klich, Wanda Olech, Krzysztof Anusz, Anna M. Pyziel

“…The study provides the first available set of specular lengths of the gastric nematodes of European bison, and the first molecular data of O. kolchida and S. boehmi derived from the same host species. …”
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Passive Indoor People Counting by Bluetooth Signal Deformation Analysis with Deep Learning by Giancarlo Iannizzotto, Lucia Lo Bello, Andrea Nucita

“…The motivation behind this research is the need for non-intrusive, privacy-preserving occupancy monitoring in sensitive indoor settings, where traditional camera-based solutions may be unsuitable. …”
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Determining the feasibility of calculating pancreatic cancer risk scores for people with new-onset diabetes in primary care (DEFEND PRIME): study protocol by Simon de Lusignan, Agnieszka Lemanska, Natalia Khalaf, Adam Harvey-Sullivan, Hugh Claridge, Claire A Price, Rofique Ali, Elizabeth A Cooke, Catherine Hodges, Dean O’Callaghan, Ali Stunt, Spencer A Thomas, Joanna Thomson

“…Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort’s demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC’s effectiveness for the early detection of pancreatic cancer.Ethics and dissemination This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). …”
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Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite by Hassan Rasoulzadeh, Hossein Azarpira, Mojtaba Pourakbar, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Prior to applying machine learning models, preprocessing steps were performed, including normalization using Min–Max Scaling to confine all features within the [0,1] range, outlier detection and removal of anomalous values, correlation analysis to avoid redundancy and multicollinearity, and data splitting into training and testing sets at an 80:20 ratio, along with K-fold cross-validation (k = 5) for robust model evaluation. …”
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Global Transcriptome and Correlation Analysis Reveal Cultivar-Specific Molecular Signatures Associated with Fruit Development and Fatty Acid Determination in Camellia oleifera Abel by Shaofeng Peng, Jia Lu, Zhen Zhang, Li Ma, Caixia Liu, Yongzhong Chen

“…The multiple phenotypic data revealed the dynamic law of changes during the picking stage. …”
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AI bias in lung cancer radiotherapy by Kai Ding, Shelby Forbes, Fangfang Ma, Ganxi Luo, Jiayou Zhou, Yian Qi

“…We then used a logistic regression model to detect bias in AI-informed treatment plans. Results: The empirical results from our synthetic patient data illustrate AI bias along the lines of (1) patient demographics (specifically, age) and (2) disease classification/histology. …”
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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Advances in machine learning, deep neural networks, and multi-omics data analysis enable precise prognostication, tailored antiretroviral therapy, and early detection of drug resistance. …”
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Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis by Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong

“…However, the limited visual perception ability makes robots difficult to directly detect the complete appearance of objects. Building predefined models is also a costly procedure. …”
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Patients’ and clinicians’ views on the appropriate use of safety-netting advice in consultations—an interview study from Sweden by Sofia Trygg Lycke

“…Background A promising approach to manage clinical uncertainty and thereby reduce the risk of preventable diagnostic harm is to use safety-netting advice (ie, communicating structured information to patients about when and where to reconsult healthcare).Aim To explore clinicians’ and patients’ views on when and how safety-netting can be successfully applied in primary-care and emergency-care settings.Design and setting An exploratory qualitative research design; we performed focus groups and interviews in a Swedish setting.Participants Nine physicians working in primary or emergency care and eight patients or caregivers participated. …”
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Clinical and morphological variants of hepatitis onset with congenital cytomegalovirus and hepatitis C infection by R. A. Ushakova, O. P. Kovtun, I. E. Valamina, N. B. Blinkova, Ya. M. Krohaleva, L. M. Ziguleva, M. A. Shvarts, S. N. Tuponogov, A. M. Nikolaeva

“…We present comparative analysis of clinical – morphological data from infants with congenital cytomegalovirus and hepatitis C infection. 97 patients with hepatitis underwent a standard set of clinical and laboratory tests. …”
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Genetic Diversity and Variability in Endangered Pantesco and Two Other Sicilian Donkey Breeds Assessed by Microsatellite Markers by Salvatore Bordonaro, Anna Maria Guastella, Andrea Criscione, Antonio Zuccaro, Donata Marletta

“…This information is worth of further investigation in order to provide suitable data for conservation strategies.…”
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