Julien Issa

Dentistry — Poznan University of Medical Sciences, Poland

LeadR Profile

86 ScienceLeadR Reputation 86
Network Map

Dentistry

Subspecialties: Medical Imaging - Informatics

Full career – Last 3 years

Main Topics

Publications and Clinical Studies

Publications – Clinical Studies

Profile data updated on

Organizations

Career arc: 2026 - 2026

Source: PubMed

Vrije Universiteit Amsterdam

could not re-read experiences after save", error); return null; } if (persistedEntries === null) { return null; } if (persistedEntries.length === 0 && sent.some((entry) => entry.isvisible !== false)) { console.warn(" re-read after save came back empty, keeping the edited entries"); return null; } this.state.current.experience = persistedEntries; const expected = this.yearsSignature(sent); const received = this.yearsSignature(persistedEntries.map((entry) => ({ isvisible: entry.isvisible, topresent: entry.topresent, year_start: entry.startperiod, year_stop: entry.endperiod }))); if (expected !== received) { console.error(" saved experiences were not persisted as sent", { sent: expected, received: received }); return false; } return true; }, async fetchExperiences() { const response = await $.ajax({ url: ajaxLoadUserData, type: "POST", data: { security: ajaxDataLoadUserData.security, data_to_load: "OrganizationHisto", } }); const parsedData = JSON.parse(response); if (parsedData.loaded === false || !parsedData.user_data || !Array.isArray(parsedData.user_data)) { return null; } return parsedData.user_data.map((value, index) => ({ company: value["name"], url: "", position: (value.hasOwnProperty("position") ? ( value["position"] ) : ( "" ) ), startperiod: value["year_start"], endperiod: value["year_stop"], topresent: (value.hasOwnProperty("topresent") ? ( value["topresent"] ) : ( false ) ), orgid: value["orgid"], isvisible: (value.hasOwnProperty("isvisible") ? ( value["isvisible"] ) : ( true ) ), description: "", tags: [], isOpen: false, ismain: (value.hasOwnProperty("ismain") ? ( value["ismain"] ) : ( (index === 0) ? true : false ) ) })); }, async loadDataOnMount() { this.loading = true; try { const experiences = await this.fetchExperiences(); this.loadFailed = experiences === null; if (experiences !== null) { this.state.current.experience = experiences; } } catch (error) { console.warn(" could not load experiences", error); this.loadFailed = true; } this.loading = false; } }, computed: { experience: { get() { return this.state.current.experience }, }, }, async mounted() { await this.loadDataOnMount() }, } }; })

Publications Synthesis

Sources: PubMed, OpenAlex

Number : 30

Citations

Citations: 285 1st author: 11 Last author: 0 Unique author: 0


Best Journals

Breakdown by type

Click a legend label to hide or show it in the chart.

Latest Publications

5 most recent indexed articles

Source: Pubmed

Title Journal Year Citations
Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review.
medical informatics, bias, intelligence, sleep apnea, obstructive, sleep, apnea, machine learning, signs and symptoms, deep learning, sleep apnea syndromes, diagnosis, learning, artificial intelligence
BMC Med Inform Decis Mak20250
Assessing the accuracy of artificial intelligence in mandibular canal segmentation compared to semi-automatic segmentation on cone-beam computed tomography images.
intelligence, cone-beam computed tomography, molar, tomography, dentistry, diagnosis, software, artificial intelligence, molar, third
Pol J Radiol20250
Career aspirations of dental students: insights from a multinational study using social cognitive career theory (SCCT).
societies, dental, students, dental, dentistry, income, education, dental, continuing, social cognition, education, career choice, aspirations, psychological
Front Oral Health20250
Artificial Intelligence-Assisted Segmentation of a Falx Cerebri Calcification on Cone-Beam Computed Tomography: A Case Report.
intelligence, cone-beam computed tomography, tomography, algorithms, diagnosis, learning, artificial intelligence, dura mater
Medicina (Kaunas)20240
Artificial intelligence versus semi-automatic segmentation of the inferior alveolar canal on cone-beam computed tomography scans: A pilot study.
pilot projects, pilots, intelligence, cone-beam computed tomography, tomography, dentistry, radiology, diagnosis, artificial intelligence
Dent Med Probl20242

LeadR Networks

Main global connection map