Liknande verk: DEVELOPMENT OF A CLINICAL DIAGNOSIS AND DECISION SUPPORT SYSTEM FOR CHEST RADIOGRAPHY USING CNN /
- DEVELOPMENT OF A CLINICAL DIAGNOSIS AND DECISION SUPPORT SYSTEM FOR CHEST RADIOGRAPHY USING CNN
- QUANTIFICATION OF PULMONARY EDEMA FROM CHEST RADIOGRAPHS USING DEEP CNN /
- ATTEMPTED MOVEMENT CLASSIFICATION OF SPINAL CORD INJURED PATIENTS COMBINING CNN AND LSTM NETWORK /
- DEVELOPMENT AND ASSESSMENT OF CARBOXYMETHYL CELLULOSE LOADED ZINC OXIDE NANOPARTICLES FOR ANTIBACTERIAL PROPERTIES /
- DEVELOPMENT OF S COST-EFFECTIVE AND PORTABLE COLORIMETER DEVICE /
- Decision support systems /
Tema: Biomedical Engineering
- DEVELOPMENT OF AN AMBULATORY PATIENT MONITORING SYSTEM FOR CARDIO FOR CARDIO-CRITICAL CARE /
- EXTRACTION AND PROCESSING OF BANANA PLANT ORIGIN CELLULOSE FOR BIOMEDICAL APPLICATIONS /
- DEVELOPMENT OF A MODEL OF BLOOD CIRCULATION FOR LABORATORY PURPOSE /
- AUTOMATED ANALYSIS OF PATIENT BLOOD SMEAR SAMPLE OBTAINED FROM OPTICAL MICROSCOPY /
- DESIGN AND DEVELOPMENT OF DIGITAL HEALTH RECORD SYSTEM FOR HOSPITALS /
- DESIGN AND DEVELOPMENT OF A COST-EFFECTIVE LEG PROSTHESIS /
Tema: This Thesis Paper of BME in M.Sc. Program.
- DEVELOPMENT OF CHICKEN EGG WHITE AND MUPIROCIN LOADED HYDROGEL DRESSING MATERIAL FOR INHIBITION OF BACTERIAL GROWTH /
- DEVELOPMENT OF A CLINICAL DIAGNOSIS AND DECISION SUPPORT SYSTEM FOR CHEST RADIOGRAPHY USING CNN /
- ATTEMPTED MOVEMENT CLASSIFICATION OF SPINAL CORD INJURED PATIENTS COMBINING CNN AND LSTM NETWORK /
- DEVELOPMENT OF CERAMIDE AND HONEY BASED BIODEGRADABLE DRESSING MATERIALS FOR THE APPLICATION TO BURN SKIN /
- PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /
Upphov: Magar, Bipin Thapa
Upphov: Supervised by Asst. Prof. Dr. Md. Asadur Rahman
- DEVELOPMENT OF A CLINICAL DIAGNOSIS AND DECISION SUPPORT SYSTEM FOR CHEST RADIOGRAPHY USING CNN /
- ATTEMPTED MOVEMENT CLASSIFICATION OF SPINAL CORD INJURED PATIENTS COMBINING CNN AND LSTM NETWORK /
- PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /