-
Je něco špatně v tomto záznamu ?
'Intracytoplasmic sperm injection (ICSI) paradox' and 'andrological ignorance': AI in the era of fourth industrial revolution to navigate the blind spots
P. Sengupta, S. Dutta, R. Jegasothy, P. Slama, CL. Cho, S. Roychoudhury
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu dopisy
NLK
BioMedCentral
od 2003-12-01
BioMedCentral Open Access
od 2003
Directory of Open Access Journals
od 2003
Free Medical Journals
od 2003
PubMed Central
od 2003
Europe PubMed Central
od 2003
ProQuest Central
od 2009-01-01
Open Access Digital Library
od 2003-01-01
Open Access Digital Library
od 2003-01-01
Open Access Digital Library
od 2003-01-01
Medline Complete (EBSCOhost)
od 2003-01-01
Health & Medicine (ProQuest)
od 2009-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2003
Springer Nature OA/Free Journals
od 2003-12-01
- MeSH
- asistovaná reprodukce MeSH
- intracytoplazmatické injekce spermie * MeSH
- lidé MeSH
- mužská infertilita * diagnóza genetika terapie MeSH
- sperma MeSH
- umělá inteligence MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- Publikační typ
- dopisy MeSH
The quandary known as the Intracytoplasmic Sperm Injection (ICSI) paradox is found at the juncture of Assisted Reproductive Technology (ART) and 'andrological ignorance' - a term coined to denote the undervalued treatment and comprehension of male infertility. The prevalent use of ICSI as a solution for severe male infertility, despite its potential to propagate genetically defective sperm, consequently posing a threat to progeny health, illuminates this paradox. We posit that the meteoric rise in Industrial Revolution 4.0 (IR 4.0) and Artificial Intelligence (AI) technologies holds the potential for a transformative shift in addressing male infertility, specifically by mitigating the limitations engendered by 'andrological ignorance.' We advocate for the urgent need to transcend andrological ignorance, envisaging AI as a cornerstone in the precise diagnosis and treatment of the root causes of male infertility. This approach also incorporates the identification of potential genetic defects in descendants, the establishment of knowledge platforms dedicated to male reproductive health, and the optimization of therapeutic outcomes. Our hypothesis suggests that the assimilation of AI could streamline ICSI implementation, leading to an overall enhancement in the realm of male fertility treatments. However, it is essential to conduct further investigations to substantiate the efficacy of AI applications in a clinical setting. This article emphasizes the significance of harnessing AI technologies to optimize patient outcomes in the fast-paced domain of reproductive medicine, thereby fostering the well-being of upcoming generations.
Basic Medical Sciences Department College of Medicine Ajman University Ajman UAE
Department of Biomedical Sciences College of Medicine Gulf Medical University Ajman UAE
Department of Life Science and Bioinformatics Assam University Silchar India
Faculty of Medicine Bioscience and Nursing MAHSA University Kuala Lumpur Malaysia
S H Ho Urology Centre Department of Surgery The Chinese University of Hong Kong Hong Kong China
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc24007147
- 003
- CZ-PrNML
- 005
- 20250819151216.0
- 007
- ta
- 008
- 240412s2024 enk f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1186/s12958-024-01193-y $2 doi
- 035 __
- $a (PubMed)38350931
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a enk
- 100 1_
- $a Sengupta, Pallav $u Department of Biomedical Sciences, College of Medicine, Gulf Medical University (GMU), Ajman, UAE. pallav_cu@yahoo.com $1 https://orcid.org/0000000219285048
- 245 10
- $a 'Intracytoplasmic sperm injection (ICSI) paradox' and 'andrological ignorance': AI in the era of fourth industrial revolution to navigate the blind spots / $c P. Sengupta, S. Dutta, R. Jegasothy, P. Slama, CL. Cho, S. Roychoudhury
- 520 9_
- $a The quandary known as the Intracytoplasmic Sperm Injection (ICSI) paradox is found at the juncture of Assisted Reproductive Technology (ART) and 'andrological ignorance' - a term coined to denote the undervalued treatment and comprehension of male infertility. The prevalent use of ICSI as a solution for severe male infertility, despite its potential to propagate genetically defective sperm, consequently posing a threat to progeny health, illuminates this paradox. We posit that the meteoric rise in Industrial Revolution 4.0 (IR 4.0) and Artificial Intelligence (AI) technologies holds the potential for a transformative shift in addressing male infertility, specifically by mitigating the limitations engendered by 'andrological ignorance.' We advocate for the urgent need to transcend andrological ignorance, envisaging AI as a cornerstone in the precise diagnosis and treatment of the root causes of male infertility. This approach also incorporates the identification of potential genetic defects in descendants, the establishment of knowledge platforms dedicated to male reproductive health, and the optimization of therapeutic outcomes. Our hypothesis suggests that the assimilation of AI could streamline ICSI implementation, leading to an overall enhancement in the realm of male fertility treatments. However, it is essential to conduct further investigations to substantiate the efficacy of AI applications in a clinical setting. This article emphasizes the significance of harnessing AI technologies to optimize patient outcomes in the fast-paced domain of reproductive medicine, thereby fostering the well-being of upcoming generations.
- 650 _2
- $a mužské pohlaví $7 D008297
- 650 _2
- $a lidé $7 D006801
- 650 12
- $a intracytoplazmatické injekce spermie $7 D020554
- 650 _2
- $a umělá inteligence $7 D001185
- 650 _2
- $a sperma $7 D012661
- 650 12
- $a mužská infertilita $x diagnóza $x genetika $x terapie $7 D007248
- 650 _2
- $a asistovaná reprodukce $7 D027724
- 655 _2
- $a dopisy $7 D016422
- 700 1_
- $a Dutta, Sulagna $u Basic Medical Sciences Department, College of Medicine, Ajman University, Ajman, UAE $1 https://orcid.org/0000000278935282
- 700 1_
- $a Jegasothy, Ravindran $u Faculty of Medicine, Bioscience and Nursing, MAHSA University, Kuala Lumpur, Malaysia $1 https://orcid.org/0000000164491900
- 700 1_
- $a Slama, Petr $u Laboratory of Animal Immunology and Biotechnology, Department of Animal Morphology, Physiology and Genetics, Faculty of AgriSciences, Mendel University in Brno, Brno, Czech Republic $1 https://orcid.org/000000030570259X $7 stk2007383506
- 700 1_
- $a Cho, Chak-Lam $u S. H. Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China $1 https://orcid.org/0000000325206833
- 700 1_
- $a Roychoudhury, Shubhadeep $u Department of Life Science and Bioinformatics, Assam University, Silchar, India. shubhadeep1@gmail.com $1 https://orcid.org/0000000341741852 $7 xx0334841
- 773 0_
- $w MED00008251 $t Reproductive biology and endocrinology $x 1477-7827 $g Roč. 22, č. 1 (2024), s. 22
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/38350931 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y - $z 0
- 990 __
- $a 20240412 $b ABA008
- 991 __
- $a 20250819151159 $b ABA008
- 999 __
- $a ok $b bmc $g 2081250 $s 1216914
- BAS __
- $a 3
- BAS __
- $a PreBMC-MEDLINE
- BMC __
- $a 2024 $b 22 $c 1 $d 22 $e 20240213 $i 1477-7827 $m Reproductive biology and endocrinology $n Reprod Biol Endocrinol $x MED00008251
- LZP __
- $a Pubmed-20240412