AIMC Topic: Machine Learning

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Augmented intelligence to predict 30-day mortality in patients with cancer.

Future oncology (London, England) Jun 30, 2021
An augmented intelligence tool to predict short-term mortality risk among patients with cancer could help identify those in need of actionable interventions or palliative care services. An algorithm to predict 30-day mortality risk was developed us...
Humans Artificial Intelligence Socioeconomic Factors Aged, 80 and over Neoplasms Adolescent Young Adult Decision Support Systems, Clinical Adult Male Middle Aged Risk Assessment Machine Learning Algorithms Electronic Health Records Female Reproducibility of Results Aged
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Molecular insights on ABL kinase activation using tree-based machine learning models and molecular docking.

Molecular diversity Jun 30, 2021
Abelson kinase (c-Abl) is a non-receptor tyrosine kinase involved in several biological processes essential for cell differentiation, migration, proliferation, and survival. This enzyme's activation might be an alternative strategy for treating disea...
Binding Sites Proto-Oncogene Proteins c-abl Ligands Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Machine Learning Molecular Docking Simulation Drug Design Protein Binding Molecular Structure Molecular Dynamics Simulation Humans
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Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models.

Analytical chemistry Jun 30, 2021
Fourier transform infrared spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. W...
Neural Networks, Computer Social Identification Machine Learning Algorithms Spectroscopy, Fourier Transform Infrared
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Earthquake-Induced Building-Damage Mapping Using Explainable AI (XAI).

Sensors (Basel, Switzerland) Jun 30, 2021
Building-damage mapping using remote sensing images plays a critical role in providing quick and accurate information for the first responders after major earthquakes. In recent years, there has been an increasing interest in generating post-earthqua...
Machine Learning Reproducibility of Results Earthquakes Neural Networks, Computer Artificial Intelligence
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Identification of subtypes of anticancer peptides based on sequential features and physicochemical properties.

Scientific reports Jun 30, 2021
Anticancer peptides (ACPs) are a kind of bioactive peptides which could be used as a novel type of anticancer drug that has several advantages over chemistry-based drug, including high specificity, strong tumor penetration capacity, and low toxicity ...
Humans Machine Learning Peptides Antineoplastic Agents Computational Biology Amino Acid Sequence
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Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia.

Scientific reports Jun 30, 2021
Combining microfluidics technology with machine learning represents an innovative approach to conduct massive quantitative cell behavior study and implement smart decision-making systems in support of clinical diagnostics. The spleen plays a key-role...
Lab-On-A-Chip Devices Anemia, Hemolytic, Congenital Male Microfluidic Analytical Techniques Image Processing, Computer-Assisted Humans Erythrocyte Deformability Erythrocytes Machine Learning Female
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Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

Journal of translational medicine Jun 30, 2021
BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients after radical resection is closely related to relapse. We aimed to develop models to predict the risk o...
Support Vector Machine Recurrence ROC Curve Adenocarcinoma Humans Machine Learning
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Prediction of preterm birth in nulliparous women using logistic regression and machine learning.

PloS one Jun 30, 2021
OBJECTIVE: To predict preterm birth in nulliparous women using logistic regression and machine learning.
Pregnancy Trimester, Second Premature Birth Parity Young Adult Logistic Models Retrospective Studies Humans Adult Area Under Curve Pregnancy Machine Learning ROC Curve Pregnancy Trimester, First Female Ontario
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Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved.

Journal of clinical epidemiology Jun 29, 2021
OBJECTIVE: Evaluate the completeness of reporting of prognostic prediction models developed using machine learning methods in the field of oncology.
Humans Machine Learning Models, Statistical Research Design Medical Oncology Prognosis Guidelines as Topic Biomedical Research
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Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low-dimensional space of brain dynamics.

Human brain mapping Jun 29, 2021
Large-scale brain dynamics are believed to lie in a latent, low-dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting-state data, ignoring a potentially large-and shared-portio...
Humans Machine Learning Magnetic Resonance Imaging Connectome Mental Processes Brain Adult Functional Neuroimaging
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