Decision-Level Fusion for Enhanced Microwave Breast Cancer Detection

Mohammad Ghavami; Navid Ghavami; Gianluigi Tiberi; Mehran Taghipour Gorjikolaie; Banafsheh Khalesi; Bilal Khalid

Decision-Level Fusion for Enhanced Microwave Breast Cancer Detection

Mohammad Ghavami
, Navid Ghavami
, Gianluigi Tiberi
, Mehran Taghipour Gorjikolaie
, Banafsheh Khalesi
, Bilal Khalid

Research output: Contribution to conference › Paper › peer-review

29 Downloads (Pure)

Abstract

In this paper, we present preliminary outcomes derived from a series of multicentric clinical trials focusing on microwave breast imaging using MammoWave. Specifically, we investigate the use of information fusion, i.e. combining the outputs of multiple classifiers, thereby reducing uncertainty and improving the reliability of predictions. We found that, optimally weighting selected models for a weighted voting strategy, can reach a quite balanced performance in terms of sensitivity and specificity in breast cancer detection.

Original language	English
Number of pages	3
Publication status	Published - 30 May 2025
Event	International Symposium on Medical Information and Communication Technology - Florence, Italy, Florence, Italy Duration: 28 May 2025 → 30 May 2025 https://www.ismict2025.org

Conference

Conference	International Symposium on Medical Information and Communication Technology
Abbreviated title	ISMICT 2025
Country/Territory	Italy
City	Florence
Period	28/05/25 → 30/05/25
Internet address	https://www.ismict2025.org

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Artificial Intelligence
Breast Cancer
MammoWave Device
Microwave Imaging
Optimization

Access to Document

m27481-ISMICTAccepted author manuscript, 254 KBLicence: CC BY 4.0

Cite this

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title = "Decision-Level Fusion for Enhanced Microwave Breast Cancer Detection",

abstract = "In this paper, we present preliminary outcomes derived from a series of multicentric clinical trials focusing on microwave breast imaging using MammoWave. Specifically, we investigate the use of information fusion, i.e. combining the outputs of multiple classifiers, thereby reducing uncertainty and improving the reliability of predictions. We found that, optimally weighting selected models for a weighted voting strategy, can reach a quite balanced performance in terms of sensitivity and specificity in breast cancer detection.",

keywords = "Artificial Intelligence, Breast Cancer, MammoWave Device, Microwave Imaging, Optimization",

author = "Mohammad Ghavami and Navid Ghavami and Gianluigi Tiberi and \{Taghipour Gorjikolaie\}, Mehran and Banafsheh Khalesi and Bilal Khalid",

year = "2025",

month = may,

day = "30",

language = "English",

note = "International Symposium on Medical Information and Communication Technology, ISMICT 2025 ; Conference date: 28-05-2025 Through 30-05-2025",

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TY - CONF

T1 - Decision-Level Fusion for Enhanced Microwave Breast Cancer Detection

AU - Ghavami, Mohammad

AU - Ghavami, Navid

AU - Tiberi, Gianluigi

AU - Taghipour Gorjikolaie, Mehran

AU - Khalesi, Banafsheh

AU - Khalid, Bilal

PY - 2025/5/30

Y1 - 2025/5/30

N2 - In this paper, we present preliminary outcomes derived from a series of multicentric clinical trials focusing on microwave breast imaging using MammoWave. Specifically, we investigate the use of information fusion, i.e. combining the outputs of multiple classifiers, thereby reducing uncertainty and improving the reliability of predictions. We found that, optimally weighting selected models for a weighted voting strategy, can reach a quite balanced performance in terms of sensitivity and specificity in breast cancer detection.

AB - In this paper, we present preliminary outcomes derived from a series of multicentric clinical trials focusing on microwave breast imaging using MammoWave. Specifically, we investigate the use of information fusion, i.e. combining the outputs of multiple classifiers, thereby reducing uncertainty and improving the reliability of predictions. We found that, optimally weighting selected models for a weighted voting strategy, can reach a quite balanced performance in terms of sensitivity and specificity in breast cancer detection.

KW - Artificial Intelligence

KW - Breast Cancer

KW - MammoWave Device

KW - Microwave Imaging

KW - Optimization

M3 - Paper

T2 - International Symposium on Medical Information and Communication Technology

Y2 - 28 May 2025 through 30 May 2025

ER -