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DESCRIPTION:Quantum Machine Learning Prediction Model for Retinal Conditions: Performance Analysis\nQuantum machine learning predictive models are emerging and in this study we developed a classifier to infer the ophthalmic disease from OCT images. We used OCT images of the retina in  vision threatening conditions such as choroidal neovascularization (CNV) and diabetic macular edema (DME). PennyLane an open-source software tool based on the concept of quantum differentiable programming was used mainly to train the quantum circuits. The training was tested on an IBM 5 qubits System “ibmq_belem” and 32 qubits simulator “ibmq_qasm_simulator”. The results are promising. 
X-ALT-DESC;FMTTYPE=text/html:Quantum Machine Learning Prediction Model for Retinal Conditions: Performance Analysis<br />Quantum machine learning predictive models are emerging and in this study we developed a classifier to infer the ophthalmic disease from OCT images. We used OCT images of the retina in  vision threatening conditions such as choroidal neovascularization (CNV) and diabetic macular edema (DME). PennyLane an open-source software tool based on the concept of quantum differentiable programming was used mainly to train the quantum circuits. The training was tested on an IBM 5 qubits System “ibmq_belem” and 32 qubits simulator “ibmq_qasm_simulator”. The results are promising. 
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SUMMARY:IQC Student Seminar featuring Manoj R. Naick
DTSTART;TZID=America/New_York:20220817T120000
DTEND;TZID=America/New_York:20220817T130000
DTSTAMP:20260408T183053Z
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STATUS:CONFIRMED
SEQUENCE:0
LOCATION:https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZTc4NmU1OTYtNzE3Yi00YWU1LWI5NDctOGY1MWY0NzlkNmY5%40thread.v2/0?context=%7b%22Tid%22%3a%22723a5a87-f39a-4a22-9247-3fc240c01396%22%2c%22Oid%22%3a%22f6147d9f-2842-4516-9b63-633ed427c2a9%22%7d
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