Machine learning analysis of pharmaceutical cocrystals solubility parameters in enhancing the drug properties for advanced pharmaceutical manufacturing by Tareq Nafea Alharby, Bader Huwaimel

“…This comparative evaluation offers valuable perspectives on selecting models for similar regression assignments, stressing the significance of choosing the right algorithm according to particular output demands. …”
Get full text

Artificial Intelligence Powered Automated and Early Diagnosis of Acute Lymphoblastic Leukemia Cancer in Histopathological Images: A Robust SqueezeNet-Enhanced Machine Learning Fram... by Vineet Mehan

“…The growing prevalence of acute lymphoblastic leukemia cancer worldwide underlines the critical need for early and more precise detection to counter this deadly disease. …”
Get full text

Explainable illicit drug abuse prediction using hematological differences by Aijun Chen, Yinchu Shen, Yu Xu, Jinhui Cai, Bo Ye, Jiaxue Sun, Jinze Du, Deshenyue Kong

“…Abstract This study aimed to develop a reliable and explainable predictive model for illicit drug use (IDU). The model uses a machine learning (ML) algorithm to predict IDU using hematological differences between illicit drug users (IDUr) and non-users (n-IDUr). …”
Get full text

FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning by Meng Zhang, Jiankun Ma, Zhenxi Zhang, Feng Zhou

“…Specifically, the clients extract representative features through distance-based metric screening, and the server aggregates model parameters via the FedAvg algorithm and fine-tunes the model using the collected features. …”
Get full text

A Cell Component-Related Prognostic Signature for Head and Neck Squamous Cell Carcinoma Based on the Tumor Microenvironment by Siyu Li, Yajun Gu, Junguo Wang, Dengbin Ma, Xiaoyun Qian, Xia Gao

“…In this study, we aimed to develop a cell component-related prognostic model based on TME. We screened cell component enrichments from samples in The Cancer Genome Atlas (TCGA) HNSCC cohort using the xCell algorithm. …”
Get full text

High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery by Qi Ou, Hongshuai Wang, Minyang Zhuang, Shangqian Chen, Lele Liu, Ning Wang, Zhifeng Gao

“…We employed a 3D transformer-based molecular representation learning algorithm to create the Org-Mol pre-trained model, using 60 million semi-empirically optimized small organic molecule structures. …”
Get full text

The Marine Safety Simulation based Electronic Chart Display and Information System by Xin Yu Zhang, Yong Yin, Jin YiCheng, XiaoFeng Sun, Ren HongXiang

“…The man-machine conversation method is taken to amend planned route to obtain autodeciding of feasibility according to ECDIS information, and the route monitoring algorithm is improved by enhancing its precision caused by screen coordinate conversion. …”
Get full text

Acetic Acid Production from Aspergillus terreus Isolated from Some Agricultural Soils Collected from Selected Locations within the North Gondar Zone, Amhara Region, Ethiopia by Kidist Alemayehu, Tamene Milkessa Jiru, Nega Berhane

“…A sequence similarity of 98.5% to A. terreus isolate LL2 (KIA) was obtained by comparing the Aspergillus isolate to a reference sequence in the GenBank using the BLAST algorithm. It can be concluded from this study that A. terreus isolated from agricultural soil in the north Gondar zone of Ethiopia could produce more acetic acid using barely straw as a substrate.…”
Get full text

Risk factors for osteoporosis in men aged 40 years or older: the results of the program «Osteoscreening-Russia» by O. A. Nikitinskaya, N. V. Toroptsova, E. L. Nasonov

“…The survey was conducted using a unified questionnaire. Screening also involved a densitometric study of distal forearm bone mineral density using a peripheral X-ray osteodensitometer (Osteometer Meditech DTX-200). …”
Get full text

A computer-driven ventilator liberation protocol in pediatric patients: a single-center pilot randomized controlled trial by Song Chen, Changxue Xiao, Xue Lu, Min Liao, Chengjun Liu, Feng Xu, Jing Li

“…The test group underwent ventilator liberation driven by a computerized algorithm combining protocolized screening, air leak testing, and spontaneous breathing testing. …”
Get full text

Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

“…The principal predictive feature variables were sex, maximum heart rate, and ST/HR index. Our model generated results within one minute after completing ExECG.ConclusionThe multimodal AI algorithm, leveraging deep learning techniques, efficiently and accurately identifies patients with significant CAD using ExECG data, aiding clinical screening in both symptomatic and asymptomatic patients. …”
Get full text

IMPROVEMENT OF ADAPTATION TO STRUCTURES REMOVABLE DENTURES IN PATIENTS WITH ISCHEMIC HEART DISEASE by N.A. Ryabushko, V.N. Dvornik, I.V. Pavlish, G.N. Balya

“…The proposed health care was a complex algorithm to use: softener oral "Corsodyl" - 3-5 times a day after meals; clean teeth and dentures 2 times a day (morning and bedtime) toothpaste "Parodontax" and the bath solution Rinhra 3-5 times a day, with dryness in the mouth For the functional assessment made dentures were designed by us and proposed to use two methods of assessing patients to adapt designs removable dentures: • Objective evaluation - "Method of determining the degree of adaptation to the designs of removable dentures," Ukraine patent for utility model №101852 of 12.10.15; • Subjective evaluation - "Method of accelerated determination adaptation of patients to removable dentures designs using screening test" certificate of registration of copyright Ukraine №59280 15.04.2015. …”
Get full text

Mining hypertension predictors using decision tree: Baseline data of Kharameh cohort study by abbas Rezaianzadeh, Samane Nematolahi, maryam jalali, Shayan Rezaeianzadeh, Masoumeh Ghoddusi Johari, Seyed Vahid Hosseini

“…This model can be useful for early screening and improving preventive and curative health services in health promotion. …”
Get full text

Advancements in Machine Learning (ML): Transforming the Future of Blood Cancer Detection and Outcome Prediction by Wiebke Rösler, Michael Roiss, Corinne Widmer

“…The diagnosis and treatment of hematologic malignancies are becoming more and more complex. Growing knowledge of pathophysiology, diagnostic methods and, last but not least, treatment options offer many opportunities for patients, but integrating the growing amount of knowledge into daily practice can be challenging. …”
Get full text

Artificial Intelligence in Biomedical Sciences: A Scoping Review by Rasha Abu-El-Ruz, Ali Hasan, Dima Hijazi, Ovelia Masoud, Atiyeh M. Abdallah, Susu M. Zughaier, Maha Al-Asmakh, Maha Al-Asmakh

“…Scope (6): Opportunities and limitations of AI in biomedical sciences, where major reported opportunities include efficiency, accuracy, universal applicability, and real-world application. Limitations include; model complexity, limited applicability, and algorithm robustness.ConclusionAI has generally been under characterized in the biomedical sciences due to variability in AI models, disciplines, and perspectives of applicability.…”
Get full text

A beginner’s approach to deep learning applied to VS and MD techniques by Stijn D’Hondt, José Oramas, Hans De Winter

“…There are many ways in which DL can be applied to these molecular modelling techniques to achieve more accurate results in a more efficient manner or expedite the data analysis of the acquired results. …”
Get full text

Module Partition of Mechatronic Products Based on Core Part Hierarchical Clustering and Non-Core Part Association Analysis by Shuai Wang, Yi-Fei Song, Guang-Yu Zou, Jia-Xiang Man

“…Firstly, the core part screening method is used to simplify the structural model of mechatronic products and reduce the difficulty of modeling. …”
Get full text

Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints by Xiumin Liu, Xinyue Zhang, Ye Sheng, Zihe Zhang, Pan Xiong, Xuehai Ju, Junwu Zhu, Caichao Ye

“…The random forest (RF) algorithm exhibited the best predictive performance for material design and screening. …”
Get full text

Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices by Chao Ping Wu, Rachel Benish Shirley, Alex Milinovich, Kaiyin Liu, Eduardo Mireles-Cabodevila, Hassan Khouli, Abhijit Duggal, Anirban Bhattacharyya

“…It also highlights ML models can serve as a promising screening tool to enhance ICU discharge, presenting a pathway toward more efficient and reliable critical care decision-making.…”
Get full text

Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

“…In medical imaging, deep learning algorithms, especially those trained with genetic algorithms, have demonstrated immense promise to improve the accuracy of pneumonia and COVID-19 diagnosis from chest X-rays. …”
Get full text