10.3390/cryst13071149
10.3390/cryst13071149 · doi-reference
Advances in AFM for the electrical characterization of semiconductors
10.1088/0034-4885/71/7/076501 · doi-reference
Rise of deep learning clinical applications and challenges in omics data: a systematic review
10.3390/diagnostics13040664 · doi-reference
10.1126/science.aaw1219
10.1126/science.aaw1219 · doi-reference
10.1158/1078-0432.ccr-13-1253
10.1158/1078-0432.ccr-13-1253 · doi-reference
10.1002/cbic.201900394
10.1002/cbic.201900394 · doi-reference
Chemically characterizing the cortical cell nano-structure of human hair using atomic force microscopy integrated with infrared spectroscopy (AFM-IR)
10.1111/ics.12753 · doi-reference
Molecular perturbation effects in AFM-based tip-enhanced raman spectroscopy: contact versus tapping mode
10.1021/acs.analchem.1c03004 · doi-reference
Tip-enhanced Raman spectroscopy with amplitude-controlled tapping-mode AFM
10.1038/s41598-022-17170-7 · doi-reference
10.1016/j.csbj.2021.08.011
10.1016/j.csbj.2021.08.011 · doi-reference
10.1016/j.csbj.2021.09.001
10.1016/j.csbj.2021.09.001 · doi-reference
10.1016/j.patter.2022.100672
10.1016/j.patter.2022.100672 · doi-reference
Locating critical events in AFM force measurements by means of one-dimensional convolutional neural networks
10.1038/s41598-022-17124-z · doi-reference
Artificial neural network-aided computational approach for mechanophenotyping of biological cells using atomic force microscopy
10.1115/1.4056916 · doi-reference
FC_analysis: a tool for investigating atomic force microscopy maps of force curves
10.1186/s12859-018-2265-4 · doi-reference
OpenFovea: open-source AFM data processing software
10.1038/nmeth.2112 · doi-reference
Detection and classification of hepatocytes and hepatoma cells using atomic force microscopy and machine learning algorithms
10.1002/jemt.24384 · doi-reference
Computer-assisted cystoscopy diagnosis of bladder cancer
10.1016/j.urolonc.2017.08.026 · doi-reference
Machine learning allows for distinguishing precancerous and cancerous human epithelial cervical cells using high-resolution AFM imaging of adhesion maps
10.3390/cells12212536 · doi-reference
10.1016/j.jcmg.2020.07.015
10.1016/j.jcmg.2020.07.015 · doi-reference
10.2196/jmir.5870
10.2196/jmir.5870 · doi-reference
A fully-automated neural network analysis of AFM force-distance curves for cancer tissue diagnosis
10.1063/1.4996300 · doi-reference
Efficient spatial sampling for AFM-based cancer diagnostics: a comparison between neural networks and conventional data analysis
10.3390/condmat4020058 · doi-reference
Application of self-organizing maps to AFM-based viscoelastic characterization of breast cancer cell mechanics
10.1038/s41598-023-30156-3 · doi-reference
Atomic force microscopy-based assessment of multimechanical cellular properties for classification of graded bladder cancer cells and cancer early diagnosis using machine learning analysis
10.1016/j.actbio.2022.12.035 · doi-reference
Mechanomics biomarker for cancer cells unidentifiable through morphology and elastic modulus
10.1021/acs.nanolett.1c00003 · doi-reference
10.1039/d0ra06255c
10.1039/d0ra06255c · doi-reference
Identification of geometrical features of cell surface responsible for cancer aggressiveness: machine learning analysis of atomic force microscopy images of human colorectal epithelial cells
10.3390/biomedicines11010191 · doi-reference
10.1073/pnas.1816459115
10.1073/pnas.1816459115 · doi-reference
10.1038/s41467-023-39085-1
10.1038/s41467-023-39085-1 · doi-reference
John McCarthy: father of AI
10.1109/mis.2002.1039837 · doi-reference
Mapping heterogeneity of cellular mechanics by multi-harmonic atomic force microscopy
10.1038/s41596-018-0031-8 · doi-reference
10.1038/nnano.2011.186
10.1038/nnano.2011.186 · doi-reference
10.1016/j.jmbbm.2011.08.020
10.1016/j.jmbbm.2011.08.020 · doi-reference
10.1073/pnas.1415348112
10.1073/pnas.1415348112 · doi-reference
Analysis of phellinus igniarius effects on gastric cancer cells by atomic force microscopy
10.1016/j.micron.2022.103376 · doi-reference
Silver nanoparticles induce cell death of colon cancer cells through impairing cytoskeleton and membrane nanostructure
10.1016/j.micron.2019.102750 · doi-reference
Mechanical properties of CTCs in patients with diagnosed ovarian cancer
10.1016/j.jbiomech.2023.111831 · doi-reference
Study of morphological and mechanical features of multinuclear and mononuclear SW480 cells by atomic force microscopy
10.1002/jemt.22950 · doi-reference
Anticancer activity of VmCT1 analogs against MCF-7 cells
10.1111/cbdd.13123 · doi-reference
