The role of nanomedicine and artificial intelligence in cancer health care: individual applications and emerging integrations—a narrative review by Prasanthi Samathoti, Rajasekhar Komarla Kumarachari, Sarad Pawar Naik Bukke, Eashwar Sai Komarla Rajasekhar, Ashish Ashokkumar Jaiswal, Zohre Eftekhari

“…Nanomedicine leverages nanoparticles for targeted drug delivery, enhancing therapeutic efficacy while minimizing adverse effects. Concurrently, AI algorithms facilitate early cancer detection, personalized treatment planning, and predictive analytics, thereby optimizing clinical outcomes. …”
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Implementasi Algoritma Random Forest Untuk Menentukan Penerima Bantuan Raskin by Ilham Kurniawan, Duwi Cahya Putri Buani, Abdussomad Abdussomad, Widya Apriliah, Rizal Amegia Saputra

“…The purpose of this study is to find the highest accuracy among the predictive classification algorithms proposed by Raskin beneficiaries using python machine learning tools and implemented through a website. …”
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The 3D tooth model segmentation method based on GAC+PointMLP network by Jianjun Chen, Liyuan Zheng, Huilai Zou, Jiafa Mao, Weiguo Sheng

“…Compared to other traditional segmentation algorithms, the proposed method shows improvements of 1.1, 2.04, 1.06, 2.2, and 1.8 percentage points in Overall Accuracy (OA), Sensitivity (SEN), Positive Predictive Value (PPV), and Intersection Over Union (IoU), respectively. …”
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High-resolution Annual Dynamic dataset of Curve Number from 2008 to 2021 over Conterminous United States by Qiong Wu, John J. Ramirez Avila, Jia Yang, Cunxiong Ji, Shanmin Fang

“…This developed CN dataset can be used as input for hydrological models or machine learning algorithms to simulate rainfall-runoff across multiple spatiotemporal scales.…”
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The Machine Learning-Based Task Automation Framework for Human Resource Management in MNC Companies by Suchitra Deviprasad, N. Madhumithaa, I. Walter Vikas, Archana Yadav, Geetha Manoharan

“…MNCs are now beginning to use ML algorithms in combination with Artificial Intelligence (AI) to streamline the HR processes. …”
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Tuberculosis Preventive Treatment (TPT) in India: A Qualitative Review by Jay Patel, Abhishek Sen, Sandeep Rai, Harsh Shah, Nisarg Desai

“…The integration of TB infection algorithm in existing TB diagnostic and treatment algorithms and comprehensive active case findings could result in positive outcome in reduction of TB, advancing India’s goal of TB elimination.…”
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Research on business oriented 5G base station energy saving system based on AI deep learning by Mengqiang XU

“…Due to the needs of 5G business development, the number of 5G base stations has increased, resulting in a sharp increase in the electricity cost of operators.Energy saving and consumption reduction has become the sustainable development demand of operators.Based on the research of mainstream 5G base station energy-saving mode and multi-directional 5G energy-saving scheme, a 5G base station energy-saving system based on a variety of AI algorithms was proposed.Through the high-precision service identification at the level of single SIM card, the best strategy of 5G base station flexible energy-saving was realized on the basis of ensuring the stable operation of 5G important services and other types of services.…”
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An Axial Compression Transformer for Efficient Human Pose Estimation by Wen Tan, Haixiang Zhang, Xinyi Song

“…In the COCO dataset experiment, there was a significant reduction in computational cost compared to those of state-of-the-art transformer-based algorithms.…”
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scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis. by Wei Lan, Tongsheng Ling, Qingfeng Chen, Ruiqing Zheng, Min Li, Yi Pan

“…The scMoMtF can simultaneously solve multiple key tasks of single-cell multi-omics data including dimension reduction, cell classification and data simulation. …”
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Research on business oriented 5G base station energy saving system based on AI deep learning by Mengqiang XU

“…Due to the needs of 5G business development, the number of 5G base stations has increased, resulting in a sharp increase in the electricity cost of operators.Energy saving and consumption reduction has become the sustainable development demand of operators.Based on the research of mainstream 5G base station energy-saving mode and multi-directional 5G energy-saving scheme, a 5G base station energy-saving system based on a variety of AI algorithms was proposed.Through the high-precision service identification at the level of single SIM card, the best strategy of 5G base station flexible energy-saving was realized on the basis of ensuring the stable operation of 5G important services and other types of services.…”
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Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities by Nourhan Zayed, Heba A. Elnemr

“…The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. …”
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Research Progress on Reducing Metal Artifacts in CT Imaging by Danyang SU, Ping HOU, Haoran ZHANG, Yuanbo MA, Jinlong LIU, Xiaopeng YANG

“…With the development of CT, metal artifact reduction technology and virtual monoenergetic imaging technology are helpful to reduce metal artifacts in CT imaging. …”
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Quantum state preparation via piecewise QSVT by Oliver O'Brien, Christoph Sünderhauf

“…Efficient state preparation is essential for implementing efficient quantum algorithms. Whilst several techniques for low-cost state preparation exist, this work facilitates further classes of states, whose amplitudes are well approximated by piecewise polynomials. …”
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Anomaly detection of large scale network based on data streams by ZHENG Jun, HU Ming-zeng, YUN Xiao-chun, ZHENG Zhong

“…The anomaly detection algorithms of the large scale network（LSN） were required to analysis the vast network traffic of G bit level in real-time and on-the-fly.A novel monitoring mechanism of LSN anomaly detection based on the data stream approach was proposed.The main contributions included: the sketch data structure and the frequent sketch algorithm of data streams were designed for anomaly detection of LSN.Optimized query methods were designed for customizing the security monitoring and detection policy with the correlations of multi data streams.The data reduction was proposed to make it possible that the whole network traffic character could be got using a few of special data streams.The experiments of the real networking environments validate the effectivity of LSN anomaly detection methods.…”
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Performance of artificial neural networks and traditional methods in determining selected growth parameters of Alburnus sellal Heckel, 1843 by Ozcan Ebru Ifakat

“…In this study, predictions were made on the growth performance of Alburnus sellal Heckel, 1843 from the Munzur River using back propagation artificial neural networks and ANN algorithms. …”
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Exploring entropy measures with topological indices on colorectal cancer drugs using curvilinear regression analysis and machine learning approaches. by Maria Fazal, Salma Kanwal, Muhammad Taskeen Raza, Asima Razzaque

“…Additionally, we propose the integration of machine learning (ML) techniques to further enhance the predictive accuracy and robustness of our models. By leveraging advanced ML algorithms, we aim to uncover more complex, non-linear relationships between topological indices and drug efficacy, potentially leading to more accurate predictions and better-informed drug design strategies.…”
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The good and the bad: using C reactive protein to distinguish bacterial from non-bacterial infection among febrile patients in low-resource settings by Camille Escadafal, Sabine Dittrich, Sandra Incardona, B Leticia Fernandez-Carballo

“…In brief, the literature that was reviewed suggests that CRP testing may be beneficial in low-resource settings to improve rational antibiotic use for febrile patients, but the positive predictive value is insufficient to allow it to be used alone as a single tool. …”
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False-positive tolerant model misconduct mitigation in distributed federated learning on electronic health record data across clinical institutions by Maxim Edelson, Anh Pham, Tsung-Ting Kuo

“…Abstract As collaborative Machine Learning on cross-institutional, fully distributed networks become an important tool in predictive health modeling, its inherent security risks must be addressed. …”
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Use of Data Mining for Intelligent Evaluation of Imputation Methods by David Red, Carlos R. Primorac

“…An additional advantage of the proposed methodology is that it provides predictive data mining models that can be used a posteriori.…”
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Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach by Mohamed Koubàa, Abdullah S. Karar, Faouzi Bahloul

“…In cloud computing environments, SVMs represent anticipated resource requirements derived from historical data, usage trends, and predictive analytics, allowing cloud providers to optimize resource allocation for maximum efficiency. …”
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