Boden MA. Sztuczna Inteligencja. Wydawnictwo Uniwersytetu Łódzkiego, Łódź 2020; 1: 14. Bosek L. Artykuł 6. w: Ustawa o prawach pacjenta i Rzeczniku Praw Pacjenta. Komentarz. Leszek Bosek (red.). Warszawa. 2020; 116-141. Buchanan BG. A (Very) Brief History of Artificial Intelligence In: AI Magazine. 2005; 26(4): 53-60. Baothman F. Artificial Intelligence Effects on Contracts and Contracting. Innovative and Agile Contracting for Digital Transformation and Industry 4.0. IGI Global, 2021; 149-160. Salto-Tellez M, Maxwell P, Hamilton P. Artificial intelligence-the third revolution in pathology. Histopathology 2019; 74: 372-376. Farabet C, Couprie C, Najman L, Lecun Y. Learning hierarchical features for scene labeling. IEEE Trans Pattern Anal Mach Intell. 2013; 35(8): 1915-1929. Kumar Y, Koul A, Singla R, Ijaz MF. Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda. J Ambient Intell Humaniz Comput. 2023; 14(7): 8459-8486. Piraianu A-I, Fulga A, Musat CL, Ciobotaru O-R, Poalelungi DG, Stamate E, Ciobotaru O, Fulga I. Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine. Diagnostics. 2023; 13(18): 2992 Lee SI, Celik S, Logsdon BA, Lundberg SM, Martins TJ, Oehler VG, Estey EH, Miller CP, Chien S, Dai J, Saxena A, Blau CA, Becker PS. A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. Nat Commun. 2018; 9(1): 42. Bann S, Khan M, Hernandez J, Munz Y, Moorthy K, Datta V, Rockall T, Darzi A. Robotics in surgery. J Am Coll Surg. 2003; 196(5): 784-795. Yang S, Zhu F, Ling X, Liu Q, Zhao P. Intelligent Health Care: Applications of Deep Learning in Computational Medicine. Front Genet. 2021;12: 607471. Wang J, Teng C, Zhang Z, Chen W, Tan J, Pan Y, Zhang R, Zhou H, Ding B, Cheng HM, Liu B. A Scalable Artificial Neuron Based on Ultrathin Two-Dimensional Titanium Oxide. ACS Nano. 2021; 15(9): 15123-15131. Emmert-Streib F, Yli-Harja O, Dehmer M. Explainable artificial intelligence and machine learning: A reality rooted perspective. WIREs Data Mining Knowl Discov. 2020; 10:e1368. Angelov PP, Soares EA, Jiang R, Arnold NI, Atkinson PM. (Explainable artificial intelligence: an analytical review. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2021; 11(5): e1424. Stata R, Bharat K, Maghoul F. The Term Vector Database: fast access to indexing terms for Web pages, Computer Networks, 2000; 33(1-6): 247-255. Parai JL, Milroy CM. Histological Aging of Bruising: A Historical and Ongoing Challenge. Academic Forensic Pathology. 2015; 5(2): 266-272. Nash KR, Sheridan DJ. Can one accurately date a bruise? State of the science. J Forensic Nurs. 2009; 5(1): 31-37. Ross CG, Langlois NEI, Heath K, Byard RW. Further evidence for a lack of reliability in the histologic ageing of bruises – an autopsy study. Aust J Forensic Sci. 2015; 47(2): 224-229. Barington K, Jensen HE, Skovgaard K. Forensic aspects of gene expression signatures for age determination in bruises as evaluated in an experimental porcine model. Forensic Sci Med Pathol. 2017; 13(2): 151-160. Hughes VK, Langlois NE. Use of reflectance spectrophotometry and colorimetry in a general linear model for the determination of the age of bruises. Forensic Sci Med Pathol. 2010; 6(4): 275-281. Tirado J, Mauricio D. Bruise dating using deep learning. J Forensic Sci. 2021; 66: 336-346. Jashnani KD, Kale SA, Rupani AB. Vitreous humor: biochemical constituents in estimation of postmortem interval. J Forensic Sci. 2010; 55(6): 1523-1527. Madea B. Is there recent progress in the estimation of the postmortem interval by means of thanatochemistry? Forensic Sci Int. 2005; 151(2-3): 139-149. Szeremeta M, Samczuk P, Pietrowska K, Kowalczyk T, Przeslaw K, Sieminska J, Kretowski A, Niemcunowicz-Janica A, Ciborowski M. In Vitro Animal Model for Estimating the Time since Death with Attention to Early Postmortem Stage. Metabolites. 2023; 13(1): 26. Metcalf JL. Estimating the postmortem interval using microbes: Knowledge gaps and a path to technology adoption. Forensic Sci Int Genet. 2019; 38: 211-218. Liu R, Gu Y, Shen M, Li H Zhang, K Wang, Q Wei, X Zhang, H Wu, D Yu, K Cai, W Wang, G Zhang, S Sun, Q Huang, P Wang Z. Predicting postmortem interval based on microbial community sequences and machine learning algorithms. Environ Microbiol. 2020; 22: 2273-2291. Metcalf JL, Xu ZZ, Weiss S, Lax S, Van Treuren W, Hyde ER, Song SJ, Amir A, Larsen P, Sangwan N, Haarmann D, Humphrey GC, Ackermann G, Thompson LR, Lauber C, Bibat A, Nicholas C, Gebert MJ, Petrosino JF, Reed SC, Gilbert JA, Lynne AM, Bucheli SR, Carter DO, Knight R. Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 2016; 351(6269): 158-162. Wang Z, Zhang F, Wang L, Yuan H, Guan D, Zhao R. Advances in artificial intelligence-based microbiome for PMI estimation. Front. Microbiol. 2022; 13: 1034051. Bukyya JL, Tejasvi MLA, Avinash A, P CH, Talwade P, Afroz MM, Pokala A, Neela PK, Shyamilee TK, Srisha V. DNA Profiling in Forensic Science: A Review. Glob Med Genet. 2021; 8(4): 135-143. Cossellu G, De Luca S, Biagi R. Farronato G, Cingolani M, Ferrante L, Cameriere R. Reliability of frontal sinus by cone beam-computed tomography (CBCT) for individual identification. Radiol med. 2015; 120: 1130-1136. Thurzo A, Kosnáčová HS, Kurilová V, Kosmeľ S, Beňuš R, Moravanský N, Kováč P, Kuracinová KM, Palkovič M, Varga I. Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy. Healthcare. 2021; 9(11): 1545. Saini M, Kapoor AK. Biometrics in forensic identification: applications and challenges. J Forensic Med. 2016; 1:108. Raszeja S. Badania histopatologiczne w opiniowaniu sądowo-lekarskim. Arch Med Sadowej Kryminol. 2007; 57(2): 180-183. Fattori A, Arfeuille G, Parratte T Gantzer J, Olagne J, Lannes B, Lhermitte B. Histopathological diagnosis of an intoxication. Ann Pathol. 2021; 41(6): 549-553. Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJWL Artificial intelligence in radiology. Nature Reviews Cancer 2018; 18(8): 500-510. Chang H, Jung C, Woo JI , Lee S, Cho J, Kim SW, Kwak TY. Artificial Intelligence in Pathology. Journal of pathology and translational medicine 2019; 53(1): 1-12. Rees-Channer RR, Bachman CM, Grignard L, Gatton ML, Burkot S ,Horning MP, Delahunt CB, H L, Mehanian C, Thompson CM, Woods K, Lansdell, P, Shah S, Chiodini PL. Evaluation of an automated microscope using machine learning for the detection of malaria in travelers returned to the UK. Front. Malar. 2023; 1: 1148115. Garland J, Hu M, Duffy M, Kesha K, Glenn C, Morrow P, Stables S, Ondruschka B, Da Broi U, Tse RD Classifying Microscopic Acute and Old Myocardial Infarction Using Convolutional Neural Networks. Am J Forensic Med Pathol. 2021; 42(3): 230-234. Badam RK, Sownetha T, Babu DBG, Waghray S, Reddy L, Garlapati K, Chavva S. Virtopsy: Touch-free autopsy. J Forensic Dent Sci. 2017; 9(1): 42. Woźniak K, Rzepecka-Woźniak E, Moskała A, Pohl J, Latacz K, Dybała B. Weapon identification using antemortem computed tomography with virtual 3D and rapid prototype modeling--a report in a case of blunt force head injury. Forensic Sci Int. 2012; 222 (1-3): e29-32. O’Sullivan S, Holzinger A, Zatloukal K , Saldiva P, Sajid MI, Wichmann D Machine learning enhanced virtual autopsy. Autops Case Rep. 2017; 7: 3-7. Bobbili R, Ramakrishna B, Madhu V. An Artificial Intelligence Model for Ballistic Performance of Thin Plates. Mech. Based Des. Struct. Mach. 2023; 51: 327-338. Cheng W, Ng CA. Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List. Environ Sci Technol. 2019; 53(23): 13970-13980. McCoubrey LE, Elbadawi M, Orlu M, Gaisford S, Basit AW. Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria. Pharmaceutics. 2021; 13(7): 1026. Wang YW, Huang L, Jiang SW, Li K, Zou J, Yang SY. CapsCarcino: A novel sparse data deep learning tool for predicting carcinogens. Food Chem Toxicol. 2020; 135: 110921. Karim A, Riahi V, Mishra A, Newton MAH, Dehzangi, A, Balle, T, Sattar A. Quantitative toxicity prediction via meta ensembling of multitask deep learning models. ACS Omega. 2021; 6: 12306-12317. Lin Z, Chou WC. Machine Learning and Artificial Intelligence in Toxicological Sciences. Toxicol Sci. 2022; 189(1): 7-19. Boehme AK, Esenwa C, Elkind MS. Stroke Risk Factors, Genetics, and Prevention. Circ Res. 2017; 120(3): 472-495. Sundaram AM, Budjakoski N, Klodmann J, Roa MA. Task-specific robot base pose optimization for robot-assisted surgeries. Front Robot AI. 2022; 9: 899646. Ustawa z dnia 9.10.2015 r., o zmianie ustawy o systemie informacji w ochronie zdrowia oraz niektórych innych ustaw – art. 42 ust. 1 u.z.l. (Dz.U. z 2015 r., poz. 1991). Art. 9 KEL, https://nil.org.pl/dokumenty/kodeks-etyki-lekarskiej Rozporządzenie Ministra zdrowia z dnia 19.07.2022 r., w sprawie programu pilotażowego w zakresie wykorzystania opasek telemedycznych w podstawowej opiece zdrowotnej (Dz.U. z 2021 r., poz. 1328). Rozporządzenie Ministra Zdrowia w sprawie programu pilotażowego w zakresie wykorzystania elektronicznych spirometrów w podstawowej opiece zdrowotnej i ambulatoryjnej opiece specjalistycznej z dnia 31.12.2021 r. (Dz.U. z 2022 r., poz. 121). Rozporządzenie Ministra Zdrowia z 6.04.2020 r., zmieniające rozporządzenie w sprawie świadczeń gwarantowanych z zakresu ambulatoryjnej opieki specjalistycznej (Dz.U. z 2020 r., poz. 612). Moschovas MC, Brady I, Jaber AR, Zeinab MA, Kaviani A, Kaouk J, Crivellaro S, Joseph J, Mottrie A, Patel V. Da Vinci SP radical prostatectomy: a multicentric collaboration and step-by-step techniques. Int Braz J Urol. 2022; 48(4): 728-729. Uk Bae S. Current Status and Future of Robotic Surgery for Colorectal Cancer-An English Version. J Anus Rectum Colon. 2022; 6(4): 221-230. Cui H, Liu GX, Deng H, Cao B, Zhang W, Liang WQ, Xie TY, Zhang QP, Wang N, Chen L, Wei B. [Comparison of short-term efficacy between robotic and 3D laparoscopic-assisted D2 radical distal gastrectomy for gastric cancer]. Zhonghua Wei Chang Wai Ke Za Zhi. 2020; 23(4): 350-356. Da Col T, Caccianiga G, Catellani M, Mariani A, Ferro M, Cordima G, De Momi E, Ferrigno G, de Cobelli O. Automating Endoscope Motion in Robotic Surgery: A Usability Study on da Vinci-Assisted Ex Vivo Neobladder Reconstruction. Front Robot AI. 2021;8:707704. Cheng Q, Dong Y. Da Vinci Robot-Assisted Video Image Processing under Artificial Intelligence Vision Processing Technology. Comput Math Methods Med. 2022; 2022: 2752444. Art. 331 k.c. (Dz.U. z 2023 r. poz. 1610). Art. 4491 § 2 k.c. (Dz.U. z 2023 r. poz. 1610). Art. 34 Ustawa z dnia 5 grudnia 1996 r. o zawodach lekarza i lekarza dentysty (Dz.U. z 1997 r. nr 28 poz. 152). Art. 35 Ustawa z dnia 5 grudnia 1996 r. o zawodach lekarza i lekarza dentysty (Dz.U. z 1997 r. nr 28 poz. 152).