Depression Detection and Diagnosis Based on Electroencephalogram (EEG) Analysis: A Systematic Review by Kholoud Elnaggar, Mostafa M. El-Gayar, Mohammed Elmogy

“…By focusing on studies that integrate EEG with machine learning (ML) and deep learning (DL) techniques, we systematically analyze methods utilizing EEG signals to identify depression biomarkers. …”
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Soil carbon-food synergy: sizable contributions of small-scale farmers by Toshichika Iizumi, Nanae Hosokawa, Rota Wagai

“…Methods We applied random forest machine learning models to global gridded datasets on crop yield (wheat, maize, rice, soybean, sorghum and millet), soil, climate and agronomic management practices from the 2000s (n = 1808 to 8123). …”
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Determination of Electrolytes in Critical Illness Patients at Different pH Ranges: Whom Shall We Believe, the Blood Gas Analysis or the Laboratory Autoanalyzer? by Christopher Hohmann, Roman Pfister, Kathrin Kuhr, Julia Merkle, Julian Hinzmann, Guido Michels

“…Data from our single-center study indicate that urgent and vital decisions based on potassium measurements can be made by trusting the value obtained on the ABG machine irrespective of pH values.…”
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A Comparison between Two Different Remineralizing Agents against White Spot Lesions: An In Vitro Study by Hassan Alsubhi, Mohammad Gabbani, Abdulsalam Alsolami, Mohammed Alotaibi, Jameel Abuljadayel, Waleed Taju, Omair Bukhari

“…The surface microhardness (SMH) was measured using the Vickers microhardness testing machine at baseline, after demineralization, and after treatment. …”
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Unleashing the potential of chatbots in mental health: bibliometric analysis by Qing Han, Chenyang Zhao

“…High-frequency terms such as “ChatGPT”, “machine learning”, and “large language models” underscore the current state of research, highlighting the cutting-edge advancements and frontiers in this field.ConclusionsThis study provides an in-depth analysis of the most prominent countries, institutions, publications, collaboration status, and research topics associated with utilization of chatbots in mental health over the last decade. …”
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Effect of ultrasonic amplitude on microstructure and properties of wire arc additive manufactured ultra-high strength steel deposited metal by Tianli Zhang, Weifeng Li, Wen Wu, Lianyong Xu, Donghai Hu, Geng Chen, Wei Li, Erika Hodúlová

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Development and biomechanical evaluation of a 3D printed analogue of the human lumbar spine by Siril Teja Dukkipati, Mark Driscoll

“…Thereafter, displacement-controlled pure moments were applied in the range of ± 15° at 0.5°/sec in all bending modes using a torsion testing machine and a custom pure bending jig. Model rotation and resisting moment under loading were recorded to quantify the rotational stiffness and hysteresis in the model. …”
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The Accuracy of the NSQIP Universal Surgical Risk Calculator Compared to Operation-Specific Calculators by Mark E. Cohen, PhD, Yaoming Liu, PhD, Bruce L. Hall, MD, PhD, MBA, FACS, Clifford Y. Ko, MD, MS, MSHS, FACS

“…For the N-RC, a cohort of 5,020,713 NSQIP patient records were randomly divided into 80% for machine learning algorithm training and 20% for validation. …”
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The antibiofilm effect and mechanism of silver nanowire-modified glass ionomer cement against multi-species oral biofilm by Tiantian Guo, Dai Wang, Sherry Shiqian Gao

“…Compressive strength, surface roughness, hardness, and wettability were measured by a universal testing machine, an atomic force microscope (AFM), a Vickers microhardness tester, and a contact angle meter, respectively. …”
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Fetal-BET: Brain Extraction Tool for Fetal MRI by Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus, Ali Gholipour

“…However, it poses significant challenges due to 1) non-standard fetal head positioning, 2) fetal movements during examination, and 3) vastly heterogeneous appearance of the developing fetal brain and the neighboring fetal and maternal anatomy across gestation, and with various sequences and scanning conditions. Development of a machine learning method to effectively address this task requires a large and rich labeled dataset that has not been previously available. …”
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Estimating rare disease prevalence and costs in the USA: a cohort study approach using the Healthcare Cost Institute claims data by Keith A Crandall, Christine M Cutillo, Ainslie Tisdale, Mahdi Baghbanzadeh, Reva L Stidd, Manpreet S Khural, Laurie J Hartman, Jeff Greenberg, Kevin B Zhang, Ali Rahnavard

“…Building capabilities to use machine learning to accelerate the diagnosis of RDs would vastly improve with changes to healthcare data, such as standardising data input, linking databases, addressing privacy issues and assigning ICD-10 codes for all RDs, resulting in more robust data for RD analytics.…”
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Quality of Life Philosophy IV. The Brain and Consciousness by Søren Ventegodt, Niels Jørgen Andersen, Joav Merrick

“…At organ level, the function can be understood as an extremely complex pattern machine. Finally, the brain’s function can be understood at the cognitive level as what provides consciousness through its ability to keep order in our complicated reality. …”
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Peningkatan Akurasi Mesin Penerjemah Bahasa Inggris - Indonesia dengan Memaksimalkan Kualitas dan Kuantitas Korpus Paralel by Herry Sujaini

“…Abstract The parallel corpus has a very important role in the statistical machine translator (SMT) system. The parallel corpus obtained by various sources usually has poor quality, while the quantity of parallel corpus is the main demand for good translation results. …”
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A Dynamic Modeling Approach: Simplifying DFIG Theory, Simulation, and Analysis by Mehmet Dal, Ralph M. Kennel

“…In this paper, a simple and easy-to-use modeling approach based on the basic dynamic voltage equations of an induction machine (IM) is proposed to provide a more physical and practical understanding of the dynamic behavior of DFIGs, considering the difference between stand-alone and grid-connected operations. …”
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Advancing Horticultural Crop Loss Reduction Through Robotic and AI Technologies: Innovations, Applications, and Practical Implications by H. W. Gammanpila, M. A. Nethmini Sashika, S. V. G. N. Priyadarshani

“…In horticulture crop loss reduction, AI plays a vital role when coupled with machine learning algorithms. By analyzing extensive volumes of data encompassing weather patterns, soil conditions, and occurrences of pests and diseases, AI systems can provide farmers with real-time insights and predictive models. …”
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The Effects of Whole Body Vibration on the Limits of Stability in Adults With Subacute Ankle Injury by Sonia Young, Harvey W. Wallmann, Kailey L. Quiambao, Brooke M. Grimes

“… # Methods Fifteen participants ages 19-27 years (Mean age 22±2.36) with either a Grade I or Grade II lateral ankle sprain received WBV in bilateral stance under three randomized conditions (high frequency-25 Hz, low frequency-6 Hz, and control, which consisted of bilateral stance with machine off) for six minutes over three sessions (one time per week). …”
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Factors Associated with Anemia among Children Aged 6–23 Months Attending Growth Monitoring at Tsitsika Health Center, Wag-Himra Zone, Northeast Ethiopia by Haile Woldie, Yigzaw Kebede, Amare Tariku

“…Automated hemoglobin machine was used to determine the hemoglobin level. …”
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Estimation of Prevalence of Hospital-Acquired Blood Infections among Patients Admitted at a Tertiary Hospital in Oman over a Period of Five Years: A Cross-Sectional Study by Marah El-Beeli, Yahya Al-Farsi, Abdullah Balkhair, Zakariya Al-Muharrmi, Mansoor Al-Jabri, Samir Al-Adawi

“…The study calls for the timely formulation and adoption of national HA-BSI screening and management programs centered on surveillance systems based on real-time analytics and machine learning.…”
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Deep learning based tractography with TractSeg in patients with hemispherotomy: Evaluation and refinement by Johannes Gruen, Tobias Bauer, Theodor Rüber, Thomas Schultz

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Psychological distress in adolescence and later economic and health outcomes in the United States population: A retrospective and modeling study. by Nathaniel Z Counts, Noemi Kreif, Timothy B Creedon, David E Bloom

“…<h4>Methods and findings</h4>This analysis estimated the relationship between psychological distress in those aged 15 to 17 years in 2000 and economic and health outcomes approximately 10 years later, accounting for an array of explanatory variables using machine learning-enabled methods. The cohort was from the National Longitudinal Study of Youth 1997 and nationally representative of those aged 12 to 18 years in 1997. …”
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