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1,265 results
  • Estimating and abstracting the 3D structure of feline bones using neural networks on X-ray (2D) images. [Journal Article]
    Commun Biol. 2020 Jun 30; 3(1):337.Čavojská J, Petrasch J, … Böttcher P
  • Computing 3D bone models using traditional Computed Tomography (CT) requires a high-radiation dose, cost and time. We present a fully automated, domain-agnostic method for estimating the 3D structure of a bone from a pair of 2D X-ray images. Our triplet loss-trained neural network extracts a 128-dimensional embedding of the 2D X-ray images. A classifier then finds the most closely matching 3D bon…
  • Tracking visual search demands and memory load through pupil dilation. [Journal Article]
    J Vis. 2020 Jun 03; 20(6):21.Stolte M, Gollan B, Ansorge U
  • Continuously tracking cognitive demands via pupil dilation is a desirable goal for the monitoring and investigation of cognitive performance in applied settings where the exact time point of mental engagement in a task is often unknown. Yet, hitherto no experimentally validated algorithm exists for continuously estimating cognitive demands based on pupil size. Here, we evaluated the performance o…
  • Enhancing chemogenomics with predictive pharmacology. [Journal Article]
    J Med Chem. 2020 Jun 23 [Online ahead of print]James T, Sardar A, Anighoro A
  • One of the grand challenges in contemporary chemical biology is the generation of a probe for every member of the human proteome. Probe selection and optimization strategies typically rely on experimental bioactivity data to determine the potency and selectivity of candidate molecules. However, this approach is profoundly limited by the sparsity of the known data, the annotation bias often found …
  • Validation of a digital pathology system including remote review during the COVID-19 pandemic. [Journal Article]
    Mod Pathol. 2020 Jun 22 [Online ahead of print]Hanna MG, Reuter VE, … Hameed M
  • Remote digital pathology allows healthcare systems to maintain pathology operations during public health emergencies. Existing Clinical Laboratory Improvement Amendments regulations require pathologists to electronically verify patient reports from a certified facility. During the 2019 pandemic of COVID-19 disease, caused by the SAR-CoV-2 virus, this requirement potentially exposes pathologists, …
  • SPHN - The Swiss Aging Citizen Reference (SACR). [Journal Article]
    Stud Health Technol Inform. 2020 Jun 16; 270:1168-1169.Jeong A, Bochud M, … Probst-Hensch N
  • In Switzerland by 2045, we expect 2.7 Mio citizens aged 65+ of whom 1.0 Mio. aged 80+. A priority and focus of personalized health research is therefore aging biology to extend healthy life expectancy. Novel molecular and imaging features will emerge as candidate targets for risk prediction and screening of chronic diseases. It is of utmost importance to test the clinical and public health utilit…
  • Machine Learning Explainability in Breast Cancer Survival. [Journal Article]
    Stud Health Technol Inform. 2020 Jun 16; 270:307-311.Jansen T, Geleijnse G, … Moncada-Torres A
  • Machine Learning (ML) can improve the diagnosis, treatment decisions, and understanding of cancer. However, the low explainability of how "black box" ML methods produce their output hinders their clinical adoption. In this paper, we used data from the Netherlands Cancer Registry to generate a ML-based model to predict 10-year overall survival of breast cancer patients. Then, we used Local Interpr…
  • Discovery and mechanistic characterization of a structurally-unique membrane active peptide. [Journal Article]
    Biochim Biophys Acta Biomembr. 2020 Jun 17 [Online ahead of print]Bansal S, Su WC, … Lam KS
  • Membrane active peptides (MAPs) have gained wide interest due to their far reaching applications in drug discovery and drug delivery. The search for new MAPs, however, has been largely skewed with bias selecting for physicochemical parameters believed to be important for membrane activity, such as alpha helicity, cationicity and hydrophobicity. Here we carry out a search-and-find strategy to scre…
  • Artificial intelligence and mechanistic modeling for clinical decision making in oncology. [Journal Article]
    Clin Pharmacol Ther. 2020 Jun 18 [Online ahead of print]Benzekry S
  • The amount of 'big' data generated in clinical oncology, whether from molecular, imaging, pharmacological or biological origin, brings novel challenges. To mine efficiently this source of information, mathematical models able to produce predictive algorithms and simulations are required, with applications for diagnosis, prognosis, drug development or prediction of the response to therapy. Such ma…
  • General route to design polymer molecular weight distributions through flow chemistry. [Journal Article]
    Nat Commun. 2020 Jun 18; 11(1):3094.Walsh DJ, Schinski DA, … Guironnet D
  • The properties of a polymer are known to be intrinsically related to its molecular weight distribution (MWD); however, previous methodologies of MWD control do not use a design and result in arbitrary shaped MWDs. Here we report a precise design to synthesis protocol for producing a targeted MWD design with a simple to use, and chemistry agnostic computer-controlled tubular flow reactor. To suppo…
  • Cellular Nanosponges Inhibit SARS-CoV-2 Infectivity. [Journal Article]
    Nano Lett. 2020 Jun 17 [Online ahead of print]Zhang Q, Honko A, … Zhang L
  • We report cellular nanosponges as an effective medical countermeasure to the SARS-CoV-2 virus. Two types of cellular nanosponges are made of the plasma membranes derived from human lung epithelial type II cells or human macrophages. These nanosponges display the same protein receptors, both identified and unidentified, required by SARS-CoV-2 for cellular entry. It is shown that, following incubat…
  • Predicting dengue importation into Europe, using machine learning and model-agnostic methods. [Journal Article]
    Sci Rep. 2020 Jun 16; 10(1):9689.Salami D, Sousa CA, … Capinha C
  • The geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic areas via the increasing connectivity of the global air transport network. The dynamic nature and intrinsic heterogeneity of the air transport network make it challenging to predict dengue importation. Here, we explore the capabilities of state-of-…
  • Review and Prospect of Tissue-agnostic targeted Strategies in Anticancer therapies. [Journal Article]
    Curr Top Med Chem. 2020 06 16 [Online ahead of print]Peng Y, Tao H, … Chen Z
  • Due to the increasing prevalence of cancer year by year, and the complexity and refractory nature of the disease itself, it is required to constantly innovate the development of new cancer treatment schemes. At the same time, the understanding of cancers has deepened, from the use of chemotherapy regimens with high toxicity and side effects, to the popularity of targeted drugs with specific targe…
  • Histology-agnostic drug development - considering issues beyond the tissue. [Review]
    Nat Rev Clin Oncol. 2020 Jun 11 [Online ahead of print]Pestana RC, Sen S, … Hong DS
  • With advances in tumour biology and immunology that continue to refine our understanding of cancer, therapies are now being developed to treat cancers on the basis of specific molecular alterations and markers of immune phenotypes that transcend specific tumour histologies. With the landmark approvals of pembrolizumab for the treatment of patients whose tumours have high microsatellite instabilit…
  • TRK fusion positive cancers: From first clinical data of a TRK inhibitor to future directions. [Review]
    Crit Rev Oncol Hematol. 2020 May 31; 152:103011.Roviello G, D'Angelo A, … Massi D
  • Genetic alterations of neurotrophic tropomyosin or tyrosine receptor kinase (NTRK) 1/2/3 genes generate TRK fusion proteins have been reported in a variety of adult and child cancers from diverse cell/tissue lineages. Larotrectinib, a tumour-agnostic TRK inhibitor, has shown remarkable efficacy in a novel "basket" study which has enrolled patients from infants to elderly with different TRK fusion…
  • Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation. [Journal Article]
    JMIR Med Inform. 2020 Jun 09; 8(6):e15791.Wongvibulsin S, Wu KC, Zeger SL
  • CONCLUSIONS: Through a clinically important example, we illustrate a general and simple approach to increase the clinical translation of ML through clinician-tailored visual displays of results from black box algorithms. We illustrate this general model-agnostic framework by applying it to SCD risk prediction. Although we illustrate the methods using SCD prediction with random forest, the methods presented are applicable more broadly to improving the clinical translation of ML, regardless of the specific ML algorithm or clinical application. As any trained predictive model can be summarized in this manner to a prespecified level of precision, we encourage the use of simplified visual displays as an adjunct to the complex predictive model. Overall, this framework can allow clinicians to peek inside the black box and develop a deeper understanding of the most important features from a model to gain trust in the predictions and confidence in applying them to clinical care.
  • Learning Target-Domain-Specific Classifier for Partial Domain Adaptation. [Journal Article]
    IEEE Trans Neural Netw Learn Syst. 2020 Jun 04; PPRen CX, Ge P, … Yan S
  • Unsupervised domain adaptation (UDA) aims at reducing the distribution discrepancy when transferring knowledge from a labeled source domain to an unlabeled target domain. Previous UDA methods assume that the source and target domains share an identical label space, which is unrealistic in practice since the label information of the target domain is agnostic. This article focuses on a more realist…
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