Results 141 to 150 of about 8,233,255 (298)

Astrometric Binary Classification via Artificial Neural Networks

The Astrophysical Journal
With nearly two billion stars observed and their corresponding astrometric parameters evaluated in the recent Gaia mission, the number of astrometric binary candidates has risen significantly.
Joe Smith
doaj   +1 more source

Lung-Sound Respiratory Disease Classification via Multiple-Instance Learning

IEEE Access
We propose a multi-channel multiple–instance learning (MIL) framework for automated respiratory disease classification that addresses acoustic heterogeneity among recording site conditions, handles weak supervision, and reflects spatial cues in ...
Truc Thi Kim Nguyen, Minh Dang Nhat Nguyen, Si van Nguyen, Thao Thi Nguyen Tran, Nghia Thanh Huu Ma, Hung Thanh Quach, An Le Pham, Franz Pernkopf   +7 more
doaj   +1 more source

The multifaceted roles of lysosomes in cancer

Molecular Oncology, EarlyView.
Lysosomes support cancer cell adaptation by integrating macromolecule degradation and nutrient recycling with nutrient sensing, inter‐organelle communication and immune regulation. These interconnected functions can promote tumour growth, stress tolerance and therapy resistance, while also creating context‐dependent vulnerabilities that may be ...
Jia Li, Kevin M. Ryan
wiley   +1 more source

Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis. [PDF]

Neuroimage Clin, 2020
Du Y, Hao H, Wang S, Pearlson GD, Calhoun VD.   +4 more
europepmc   +1 more source

Tumour‐proximal deep serum proteomics identifies biomarkers associated with ovarian cancer

Molecular Oncology, EarlyView.
New biomarkers are needed for early ovarian cancer detection. Ovarian (tumour‐proximal) and peripheral vein serum from healthy women and patients with benign or malignant tumours underwent nanoparticle‐enriched deep proteomics. Ovarian serum yielded more protein identifications and revealed tumour‐reflective signatures.
Darren Lau, Daniel Pincher, Clifford Young, Nicholas Chappell, Noor A. Lokman, Parul Mittal, Leigh Donnellan, Martin K. Oehler, Doug A. Brooks, Peter Hoffmann   +9 more
wiley   +1 more source

Activity recognition via classification constrained diffusion maps

, 2006
Ma, Y.; Damelin, S.B.. (2006). Activity recognition via classification constrained diffusion maps.
Damelin, S.B., Ma, Y.
core  

Binarized support vector machines [PDF]

, 2007
The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have become more popular among practitioners than SVM thanks to their ...
Martin-Barragan, Belen, Carrizosa, Emilio, Romero Morales, Dolores   +2 more
core   +1 more source

Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up

Molecular Oncology, EarlyView.
This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani, Laura Mariën, Caro De Weerdt, Sanne Wouters, Laure‐Anne Teuwen, Hans Prenen, Katleen Janssens, Timon Vandamme   +7 more
wiley   +1 more source

The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection

Molecular Oncology, EarlyView.
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński, Krzysztof Pastuszak, Anna Samelak‐Czajka, Zuzanna Cemka, Paulina Jackowiak, Tomasz Stefaniak, Sylwia Łapińska‐Szumczyk, Jacek Jassem, Anna J. Żaczek, Matthew T. Rondina, Myron G. Best, Sjors G. J. G. In 't Veld, Anna Supernat   +12 more
wiley   +1 more source

Occlusion enhanced pan-cancer classification via deep learning

BMC Bioinformatics
Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of ...
Xing Zhao, Zigui Chen, Huating Wang, Hao Sun   +3 more
doaj   +1 more source