User profiles for N. M. Krishnan
NM Anoop KrishnanAssociate Professor, Indian Institute of Technology Delhi Verified email at iitd.ac.in Cited by 2651 |
A comparison of free autologous breast reconstruction with and without the use of laser-assisted indocyanine green angiography: a cost-effectiveness analysis
A Chatterjee, NM Krishnan, MM Van Vliet… - Plastic and …, 2013 - journals.lww.com
… Laser-assisted indocyanine green angiography uses the dye indocyanine green that binds
to intravascular proteins and emits fluorescence when excited by an 805-nm laser imaging …
to intravascular proteins and emits fluorescence when excited by an 805-nm laser imaging …
The cost effectiveness of acellular dermal matrix in expander–implant immediate breast reconstruction
NM Krishnan, A Chatterjee, KM Rosenkranz… - Journal of Plastic …, 2014 - Elsevier
Background Expander–implant breast reconstruction is often supplemented with acellular
dermal matrix (ADM). The use of acellular dermal matrix has allowed for faster, less painful …
dermal matrix (ADM). The use of acellular dermal matrix has allowed for faster, less painful …
Is single-stage prosthetic reconstruction cost effective? A cost-utility analysis for the use of direct-to-implant breast reconstruction relative to expander-implant …
NM Krishnan, JP Fischer, MN Basta… - Plastic and …, 2016 - journals.lww.com
Background: Prosthetic breast reconstruction is most commonly performed using the two-stage
(expander-implant) technique. However, with the advent of skin-sparing mastectomy and …
(expander-implant) technique. However, with the advent of skin-sparing mastectomy and …
[HTML][HTML] MatSciBERT: A materials domain language model for text mining and information extraction
A large amount of materials science knowledge is generated and stored as text published in
peer-reviewed scientific literature. While recent developments in natural language …
peer-reviewed scientific literature. While recent developments in natural language …
Prediction of concrete strengths enabled by missing data imputation and interpretable machine learning
Abstract Machine learning (ML)-based prediction of non-linear composition-strength
relationship in concretes requires a large, complete, and consistent dataset. However, the …
relationship in concretes requires a large, complete, and consistent dataset. However, the …
[HTML][HTML] A draft of the genome and four transcriptomes of a medicinal and pesticidal angiosperm Azadirachta indica
Background The Azadirachta indica (neem) tree is a source of a wide number of natural
products, including the potent biopesticide azadirachtin. In spite of its widespread applications in …
products, including the potent biopesticide azadirachtin. In spite of its widespread applications in …
A new transferable interatomic potential for molecular dynamics simulations of borosilicate glasses
Borosilicate glasses are traditionally challenging to model using atomic scale simulations
due to the composition and thermal history dependence of the coordination state of B atoms. …
due to the composition and thermal history dependence of the coordination state of B atoms. …
[HTML][HTML] Predicting the Young's modulus of silicate glasses using high-throughput molecular dynamics simulations and machine learning
…, X Xu, B Yang, B Cook, H Ramos, NMA Krishnan… - Scientific reports, 2019 - nature.com
The application of machine learning to predict materials’ properties usually requires a large
number of consistent data for training. However, experimental datasets of high quality are …
number of consistent data for training. However, experimental datasets of high quality are …
[HTML][HTML] Cooling rate effects in sodium silicate glasses: Bridging the gap between molecular dynamics simulations and experiments
Although molecular dynamics (MD) simulations are commonly used to predict the structure
and properties of glasses, they are intrinsically limited to short time scales, necessitating the …
and properties of glasses, they are intrinsically limited to short time scales, necessitating the …
Predicting the dissolution kinetics of silicate glasses using machine learning
Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task
as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can …
as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can …