Application of Machine Learning in Predicting the Properties of Two-Dimensional Semiconductor Materials. [PDF]
Yang J, Tang L, Wang Y, Wen J, Chen W.
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Controlling the protein corona formation onto carbon nanomaterials (CNMs) enhances their functionalities as platforms for cancer theranostics. Here, we reviewed the effects of the intrinsic and acquired properties of CNMs on protein corona formation, the consequent biological and toxicological outcomes, and the strategies to reshape corona formation ...
Yajuan Zou +5 more
wiley +1 more source
Use of Artificial Intelligence in the Early Diagnosis of Oral Cancer: Current Update, Limitations and Future Perspectives. [PDF]
Bajpai M.
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The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
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Retraction Note: Unveiling the potential of machine learning approaches in predicting the emergence of stroke at its onset: a predicting framework. [PDF]
J M SL, P S.
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The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
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From Machine Learning to Generative Artificial Intelligence in Urology: Technological Evolution and Future Perspectives. [PDF]
Eun SJ, Park JM, Na YG.
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Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source
Development of an exploratory prediction model for preoperative CK19 expression in esophageal cancer driven by radiomics and machine learning. [PDF]
Yang J, Wang S, Chen X, Liu L, Li Y.
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