BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

232 related articles for article (PubMed ID: 35175381)

  • 41. An original deep learning model using limited data for COVID-19 discrimination: A multicenter study.
    Xu F; Lou K; Chen C; Chen Q; Wang D; Wu J; Zhu W; Tan W; Zhou Y; Liu Y; Wang B; Zhang X; Zhang Z; Zhang J; Sun M; Zhang G; Dai G; Hu H
    Med Phys; 2022 Jun; 49(6):3874-3885. PubMed ID: 35305027
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images.
    Fleury E; Marcomini K
    Eur Radiol Exp; 2019 Aug; 3(1):34. PubMed ID: 31385114
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis.
    Xu HL; Gong TT; Liu FH; Chen HY; Xiao Q; Hou Y; Huang Y; Sun HZ; Shi Y; Gao S; Lou Y; Chang Q; Zhao YH; Gao QL; Wu QJ
    EClinicalMedicine; 2022 Nov; 53():101662. PubMed ID: 36147628
    [TBL] [Abstract][Full Text] [Related]  

  • 44. An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.
    Pantanowitz L; Quiroga-Garza GM; Bien L; Heled R; Laifenfeld D; Linhart C; Sandbank J; Albrecht Shach A; Shalev V; Vecsler M; Michelow P; Hazelhurst S; Dhir R
    Lancet Digit Health; 2020 Aug; 2(8):e407-e416. PubMed ID: 33328045
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics.
    Kakileti ST; Madhu HJ; Manjunath G; Wee L; Dekker A; Sampangi S
    Artif Intell Med; 2020 May; 105():101854. PubMed ID: 32505418
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19 using pristine ground-truth, versus radiologists.
    Tan T; Das B; Soni R; Fejes M; Yang H; Ranjan S; Szabo DA; Melapudi V; Shriram KS; Agrawal U; Rusko L; Herczeg Z; Darazs B; Tegzes P; Ferenczi L; Mullick R; Avinash G
    Neurocomputing (Amst); 2022 May; 485():36-46. PubMed ID: 35185296
    [TBL] [Abstract][Full Text] [Related]  

  • 47. A New Practical Decision Rule to Better Differentiate BI-RADS 3 or 4 Breast Masses on Breast Ultrasound.
    Pfob A; Barr RG; Duda V; Büsch C; Bruckner T; Spratte J; Nees J; Togawa R; Ho C; Fastner S; Riedel F; Schaefgen B; Hennigs A; Sohn C; Heil J; Golatta M
    J Ultrasound Med; 2022 Feb; 41(2):427-436. PubMed ID: 33942358
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound:
    Yi PH; Garner HW; Hirschmann A; Jacobson JA; Omoumi P; Oh K; Zech JR; Lee YH
    AJR Am J Roentgenol; 2024 Mar; 222(3):e2329530. PubMed ID: 37436032
    [TBL] [Abstract][Full Text] [Related]  

  • 49. AI-enhanced breast imaging: Where are we and where are we heading?
    Bitencourt A; Daimiel Naranjo I; Lo Gullo R; Rossi Saccarelli C; Pinker K
    Eur J Radiol; 2021 Sep; 142():109882. PubMed ID: 34392105
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Artificial intelligence, BI-RADS evaluation and morphometry: A novel combination to diagnose breast cancer using ultrasonography, results from multi-center cohorts.
    Hamyoon H; Yee Chan W; Mohammadi A; Yusuf Kuzan T; Mirza-Aghazadeh-Attari M; Leong WL; Murzoglu Altintoprak K; Vijayananthan A; Rahmat K; Ab Mumin N; Sam Leong S; Ejtehadifar S; Faeghi F; Abolghasemi J; Ciaccio EJ; Rajendra Acharya U; Abbasian Ardakani A
    Eur J Radiol; 2022 Dec; 157():110591. PubMed ID: 36356463
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System.
    Rodríguez-Ruiz A; Krupinski E; Mordang JJ; Schilling K; Heywang-Köbrunner SH; Sechopoulos I; Mann RM
    Radiology; 2019 Feb; 290(2):305-314. PubMed ID: 30457482
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Impact of artificial intelligence in breast cancer screening with mammography.
    Dang LA; Chazard E; Poncelet E; Serb T; Rusu A; Pauwels X; Parsy C; Poclet T; Cauliez H; Engelaere C; Ramette G; Brienne C; Dujardin S; Laurent N
    Breast Cancer; 2022 Nov; 29(6):967-977. PubMed ID: 35763243
    [TBL] [Abstract][Full Text] [Related]  

  • 53. FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies.
    Ebrahimian S; Kalra MK; Agarwal S; Bizzo BC; Elkholy M; Wald C; Allen B; Dreyer KJ
    Acad Radiol; 2022 Apr; 29(4):559-566. PubMed ID: 34969610
    [TBL] [Abstract][Full Text] [Related]  

  • 54. M2AI-CVD: Multi-modal AI approach cardiovascular risk prediction system using fundus images.
    Gurumurthy P; Alagarsamy M; Kuppusamy S; Ponnusamy NC
    Network; 2024 Aug; 35(3):319-346. PubMed ID: 38279811
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Computerized detection of breast tissue asymmetry depicted on bilateral mammograms: a preliminary study of breast risk stratification.
    Wang X; Lederman D; Tan J; Wang XH; Zheng B
    Acad Radiol; 2010 Oct; 17(10):1234-41. PubMed ID: 20619697
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Computer-aided diagnosis for the classification of breast masses in automated whole breast ultrasound images.
    Moon WK; Shen YW; Huang CS; Chiang LR; Chang RF
    Ultrasound Med Biol; 2011 Apr; 37(4):539-48. PubMed ID: 21420580
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Applications of Artificial Intelligence in Breast Pathology.
    Liu Y; Han D; Parwani AV; Li Z
    Arch Pathol Lab Med; 2023 Sep; 147(9):1003-1013. PubMed ID: 36800539
    [TBL] [Abstract][Full Text] [Related]  

  • 58. A Comparative Study of Multiple Deep Learning Models Based on Multi-Input Resolution for Breast Ultrasound Images.
    Wu H; Ye X; Jiang Y; Tian H; Yang K; Cui C; Shi S; Liu Y; Huang S; Chen J; Xu J; Dong F
    Front Oncol; 2022; 12():869421. PubMed ID: 35875151
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.
    Rodriguez-Ruiz A; Lång K; Gubern-Merida A; Teuwen J; Broeders M; Gennaro G; Clauser P; Helbich TH; Chevalier M; Mertelmeier T; Wallis MG; Andersson I; Zackrisson S; Sechopoulos I; Mann RM
    Eur Radiol; 2019 Sep; 29(9):4825-4832. PubMed ID: 30993432
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Artificial Intelligence for Breast MRI in 2008-2018: A Systematic Mapping Review.
    Codari M; Schiaffino S; Sardanelli F; Trimboli RM
    AJR Am J Roentgenol; 2019 Feb; 212(2):280-292. PubMed ID: 30601029
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 12.