ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINEAI in ARTNCT05699850
ARTIFICIAL INTELLIGENCE IN REPRODUCTIVE MEDICINE
An observational study of ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE, run by Al Baraka Fertility Hospital at 2 sites in Egypt.
Trial summary
Many studies have been published investigating the use of AI as an unbiased, automated approach to embryo assessment. This review will summarize the recent AI advancements in the IVF field. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE
- What is being tested?
- ARTIFICIAL INTELLIGENCE (AI)
- How many people
- 10 participants
- Where
- 2 sitesEgypt
- Study dates
- 1 Nov 2022to 1 Apr 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: those people coming for fertility clinics
Who may be able to join
- fertility related
Who cannot join
- fertile people
Trial locations and contacts
2 sites in 1 country.
Egypt2 sites, 2 recruiting
- Recruiting
Al-Azhar university
Cairo, 12358
Dr. Mohammed Atef, M.D., 00201006206040, kimovip2000@yahoo.com
- Recruiting
Kamal Eldin Abdalla Rageh
Cairo, 15006
Kamal Eldin A Rageh, 0097333153871, dr_kamal_rageh@yahoo.com
About this study
Official title: ARTIFICIAL INTELLIGENCE APPLICATIONS IN REPRODUCTIVE MEDICINE
Many studies have been published investigating the use of AI as an unbiased, automated approach to embryo assessment. This review will summarize the recent AI advancements in the IVF field. Hopefully, that incorporating AI technology into the IVF clinics may be the next frontier in the journey towards personalised reproductive medicine and improved fertility outcomes for patients.
Read the detailed description
ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE
Kamaleldin Abdullah Rageh, M.D. (1).
Mohammad Atef Behery, M.D. (2)
Elsayed Ali Farag, M.D. (1)
1 -Department of Obstetrics and Gynecology, Faculty of medicine, Al-Azhar University, Cairo, Egypt.
2-International Islamic Center for Population Studies and Research, Al-Azhar University, Cairo, Egypt.
Abstract:
In spite of improved almost all aspects of IVF: ovarian stimulation, embryo culture and transfer, the pregnancy rates still not satisfactory. Studies confirm that up to 50% of the performed IVF cycles fail and there may be no direct explanation for this.
And it's worthy to mention that accurately predicting the outcome of an IVF cycle has yet to be achieved. One reason for this is the method of selecting an embryo for transfer. Morphological assessment of embryos is the traditional method of evaluating embryo quality and selecting which embryo to transfer. However, this subjective method of assessing embryos leads to inter- and intra-observer variability, resulting in less than optimal IVF success rates. Although time-lapse incubators and preimplantation genetic testing for aneuploidy have been introduced to help increase the chances of live birth, the outcomes remain less than ideal.
Currently, infertility treatments exert a lot of financial and emotional stress, especially in patients with previously failed IVF treatments, where there is no clear cause to be identified is a common, heartbreaking endpoint when the emotional, financial and physical burden of the treatment escalate to continue finding answers, but AI systems might help solve the dilemma by picking the best viable embryos that humans can't do. AI technologies have excellent potential to help the infertility field to soar over its current narrow focus on individual embryos and detect new patterns hidden in the patient data for overcoming the prevailing infertility cases.
The embryo selection is the most critical factor for the success of IVF. However, there is no single definitive criterion that can predict the success of an embryo. Rather, embryo selection is based on a variety of factors, making it is difficult to predict the probability of a successful pregnancy for each patient and to fully understand the cause of each failure. So, Utilization of artificial intelligence (AI) may support the clinicians in filling this knowledge gap, thereby being leveraged in the embryology laboratory to help improve IVF outcomes.
- Being tested
- ARTIFICIAL INTELLIGENCE (AI)
- Keywords
- ARTIFICIAL INTELLIGENCE (AI), IVF, ART
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ARTIFICIAL INTELLIGENCE (AI)Other
ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE
What is being measured
The primary outcome is the main question the study is designed to answer.
SUCCESS RATE
ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE
Measured: 4 MONTHS
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jan 2023
- Study start1 Nov 2022
- Primary completion1 Mar 2023 (estimated)
- Study completion1 Apr 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINEStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 10 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Al Baraka Fertility Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Al-Azhar University
- Responsible party
- Principal investigator, Dr. Kamal Rageh, MD, Al-Azhar University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05699850
- Sponsor's protocol ID
- Kamal-AI
- Acronym
- AI in ART
- Status last verified
- Jan 2023
- First submitted
- 17 Jan 2023
- Last updated
- 26 Jan 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: will think about it
Study at a glance
From the registry record, last updated by the sponsor on 26 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- ARTIFICIAL INTELLIGENCE APPLICATIONS IN REPRODUCTIVE MEDICINE
- ClinicalTrials.gov ID
- NCT05699850
- Acronym / sponsor ID
- AI in ART / Kamal-AI
- Keywords
- ARTIFICIAL INTELLIGENCE (AI), IVF, ART
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 10 participants (estimated)
- Lead sponsor
- Al Baraka Fertility HospitalUniversity, hospital or other
- Collaborators
- Al-Azhar University
- Study start
- 1 Nov 2022 (actual)
- Primary completion
- 1 Mar 2023 (estimated)
- Study completion
- 1 Apr 2023 (estimated)
- First posted
- 26 Jan 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Many studies have been published investigating the use of AI as an unbiased, automated approach to embryo assessment. This review will summarize the recent AI advancements in the IVF field. Hopefully, that incorporating AI technology into the IVF clinics may be the next frontier in the journey towards personalised reproductive medicine and improved fertility outcomes for patients.
Detailed description
ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE
Kamaleldin Abdullah Rageh, M.D. (1).
Mohammad Atef Behery, M.D. (2)
Elsayed Ali Farag, M.D. (1)
1 -Department of Obstetrics and Gynecology, Faculty of medicine, Al-Azhar University, Cairo, Egypt.
2-International Islamic Center for Population Studies and Research, Al-Azhar University, Cairo, Egypt.
Abstract:
In spite of improved almost all aspects of IVF: ovarian stimulation, embryo culture and transfer, the pregnancy rates still not satisfactory. Studies confirm that up to 50% of the performed IVF cycles fail and there may be no direct explanation for this.
And it's worthy to mention that accurately predicting the outcome of an IVF cycle has yet to be achieved. One reason for this is the method of selecting an embryo for transfer. Morphological assessment of embryos is the traditional method of evaluating embryo quality and selecting which embryo to transfer. However, this subjective method of assessing embryos leads to inter- and intra-observer variability, resulting in less than optimal IVF success rates. Although time-lapse incubators and preimplantation genetic testing for aneuploidy have been introduced to help increase the chances of live birth, the outcomes remain less than ideal.
Currently, infertility treatments exert a lot of financial and emotional stress, especially in patients with previously failed IVF treatments, where there is no clear cause to be identified is a common, heartbreaking endpoint when the emotional, financial and physical burden of the treatment escalate to continue finding answers, but AI systems might help solve the dilemma by picking the best viable embryos that humans can't do. AI technologies have excellent potential to help the infertility field to soar over its current narrow focus on individual embryos and detect new patterns hidden in the patient data for overcoming the prevailing infertility cases.
The embryo selection is the most critical factor for the success of IVF. However, there is no single definitive criterion that can predict the success of an embryo. Rather, embryo selection is based on a variety of factors, making it is difficult to predict the probability of a successful pregnancy for each patient and to fully understand the cause of each failure. So, Utilization of artificial intelligence (AI) may support the clinicians in filling this knowledge gap, thereby being leveraged in the embryology laboratory to help improve IVF outcomes.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- those people coming for fertility clinics
Key inclusion criteria (1 listed)
- fertility related
Key exclusion criteria (1 listed)
- fertile people
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ARTIFICIAL INTELLIGENCE (AI)ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE | Other | – |
Primary outcome
SUCCESS RATE
Time frame: 4 MONTHS
ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Jan 2023.
- Individual participant dataSharing planned: Undecided. will think about it
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of ARTIFICIAL INTELLIGENCE (AI) APPLICATIONS IN REPRODUCTIVE MEDICINE, run by Al Baraka Fertility Hospital at 2 sites in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 26 Jan 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
SUCCESS RATE (time frame: 4 MONTHS). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Jan 2023; AzTrials last refreshed its copy on 31 Oct 2026.