A novel machine-learning algorithm to screen for trisomy 21 in first-trimester singleton pregnancies by James Osborne, Chris Cockcroft, Carolyn Williams

“…This study investigates the use of machine-learning algorithms in the prediction of T21 in first-trimester singleton pregnancies and compares their performance to existing screening models.Methods A total of 86,354 anonymised, first trimester, singleton pregnancy screening cases, including 211 with T21, were used to train and test machine-learning models using adaptive boosting technology. …”
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Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems by Pennipat Nabheerong, Warissara Kiththiworaphongkich, Watcharaporn Cholamjiak

“…To detect breast cancer in mammography screening practice, we modify the inertial relaxed CQ algorithm with Mann’s iteration for solving split feasibility problems in real Hilbert spaces to apply in an extreme learning machine as an optimizer. …”
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Estimated inpatient malnutrition prevalence, screening tool utilization, and dietitian referral rates across hospitals during extension of phase 2 of More-2-Eat by Yingying Xu, Rachel A. Warren, Shirley M. Peters, Sonya Boudreau, Tina N. Strickland, Mari Somerville, Brenda L. MacDonald, Heather Keller, Leah E. Cahill

“…The Integrated Nutrition Pathway for Acute Care (INPAC) is a validated multi-step algorithm that includes screening using the Canadian Nutrition Screening Tool (CNST) and diagnosis using Subjective Global Assessment (SGA). …”
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ALGORITHM OF PSYCHOLOGICAL AND PSYCHOTHERAPEUTIC SUPPORT OF PATIENTS WITH CHRONIC CEREBRAL ISCHEMIA by I. V. Khianikiainen, V. A. Mikhailov

“…The objective of the study was to develop the algorithm for identifying psychosocial characteristics of patients with ES CCI and providing them with psychotherapeutic care. …”
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Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images by M. Shanmuga Eswari, S. Balamurali, Lakshmana Kumar Ramasamy

“…Objective We developed an optimized decision support system for retinal fundus image-based glaucoma screening. Methods We combined computer vision algorithms with a convolutional network for fundus images and applied a faster region-based convolutional neural network (FRCNN) and artificial algae algorithm with support vector machine (AAASVM) classifiers. …”
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A proposed algorithm for early autism screening in Polish primary care settings – a pilot study by Patryk Domarecki, Katarzyna Plata-Nazar, Wojciech Nazar

“…Abstract Background The rising rate of autism spectrum disorder (ASD) prevalence worldwide demands new screening algorithms to make the process of diagnosis more effective. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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Deep learning based screening model for hip diseases on plain radiographs. by Jung-Wee Park, Seung Min Ryu, Hong-Seok Kim, Young-Kyun Lee, Jeong Joon Yoo

“…<h4>Conclusion</h4>The deep learning-based model showed high accuracy and reliability in screening hip diseases on plain radiographs, potentially aiding physicians in more accurately diagnosing hip conditions.…”
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Sure Independence Screening for Ultrahigh-Dimensional Additive Model with Multivariate Response by Yongshuai Chen, Baosheng Liang

“…This paper investigated an ultrahigh-dimensional feature screening approach for additive models with multivariate responses. …”
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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…Based on linear regression (LR), support vector machine (SVM), decision tree (DT) and random forest (RF) algorithms, four intelligent prediction models of cross screening rate were established. …”
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Increasing clinicians’ suspicion of ATTR amyloidosis using a retrospective algorithm by Jessica Ammon, John Alexander, Woodson Petit-Frere, Deya Alkhatib, Aranyak Rawal, Grace Newman, Oguz Akbiligic, Brian Borkowski, John Jefferies, Isaac B. Rhea

“…Abstract Background This study aimed to increase the index of suspicion for transthyretin amyloidosis (ATTR) among cardiologists leading to increased screening for amyloidosis. Methods A retrospective algorithm was created to identify patients at risk for ATTR. …”
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Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies. by Cox Lwaka Tamba, Yuan-Li Ni, Yuan-Ming Zhang

“…This method is referred to as ISIS EM-BLASSO algorithm. Monte Carlo simulation studies validated the new method, which has the highest empirical power in QTN detection and the highest accuracy in QTN effect estimation, and it is the fastest, as compared with efficient mixed-model association (EMMA), smoothly clipped absolute deviation (SCAD), fixed and random model circulating probability unification (FarmCPU), and multi-locus random-SNP-effect mixed linear model (mrMLM). …”
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A novel lightweight multi-scale feature fusion segmentation algorithm for real-time cervical lesion screening by Jiahui Yang, Ying Zhang, Wenlong Fan, Jie Wang, Xinhe Zhang, Chunhui Liu, Shuang Liu, Linyan Xue

“…Therefore, a lightweight algorithm segmentation for cervical lesion real-time screening system is urgently needed. …”
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Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review by Milad Yousefi, Matin Akhbari, Zhina Mohamadi, Shaghayegh Karami, Hediyeh Dasoomi, Alireza Atabi, Seyed Amirali Sarkeshikian, Mahdi Abdoullahi Dehaki, Hesam Bayati, Negin Mashayekhi, Shirin Varmazyar, Zahra Rahimian, Mahsa Asadi Anar, Daniel Shafiei, Alireza Mohebbi

“…Machine learning aids in more precise disease identification, potentially transforming healthcare. …”
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XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis by Sudi Suryadi, Masrizal

“…This study is situated at the intersection of clinical oncology and computational intelligence, exploring the potential of gradient-boosting algorithms to overcome the limitations of conventional screening methodologies. …”
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Screening benzimidazole derivatives for atypical antipsychotic activity by K. Yu. Kalitin, O. Yu. Mukha, V. B. Voynov

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Cost-effectiveness analysis of MASLD screening using FIB-4 based two-step algorithm in the medical check-up by Mimi Kim, Huiyul Park, Eileen L. Yoon, Ramsey Cheung, Donghee Kim, Hye-Lin Kim, Dae Won Jun

“…We constructed a hybrid model of the decision tree model and Markov model to compare expected costs and quality-adjusted life-years (QALYs) between ‘screening’ and ‘no screening’ groups from healthcare system perspectives. …”
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Performance of machine learning-based models to screen obstructive sleep apnea in pregnancy by Jingyu Wang, Wenhan Xiao, Haoyang Hong, Chi Zhang, Min Yu, Liyue Xu, Jun Wei, Jingjing Yang, Yanan Liu, Huijie Yi, Linyan Zhang, Rui Bai, Bing Zhou, Long Zhao, Xueli Zhang, Xiaozhi Wang, Xiaosong Dong, Guoli Liu, Shenda Hong

“…Abstract The purpose of this study is to improve the performance of existing OSA screening tools for pregnant women with machine learning algorithms. …”
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Performance and limitation of machine learning algorithms for diabetic retinopathy screening and its application in health management: a meta-analysis by Mehrsa Moannaei, Faezeh Jadidian, Tahereh Doustmohammadi, Amir Mohammad Kiapasha, Romina Bayani, Mohammadreza Rahmani, Mohammad Reza Jahanbazy, Fereshteh Sohrabivafa, Mahsa Asadi Anar, Amin Magsudy, Seyyed Kiarash Sadat Rafiei, Yaser khakpour

“…Abstract Background In recent years, artificial intelligence and machine learning algorithms have been used more extensively to diagnose diabetic retinopathy and other diseases. …”
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Accuracy improvement in financial sanction screening: is natural language processing the solution? by Seihee Kim, ShengYun Yang

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