[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ custom_padding=”||0px|||” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ custom_padding=”12px|||||” locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ global_colors_info=”{}”][et_pb_text _builder_version=”4.18.0″ text_font=”||||||||” header_font=”Roboto||||||||” header_text_color=”#323232″ header_font_size=”40px” header_line_height=”1.2em” max_width=”85%” module_alignment=”center” custom_margin=”||19px|||” global_colors_info=”{}”]<\/p>\n
[\/et_pb_text][et_pb_divider color=”#003389″ divider_weight=”3px” _builder_version=”4.16″ width=”100%” max_width=”21%” module_alignment=”left” custom_margin=”|||0px|false|false” custom_padding=”|||80px|false|false” global_colors_info=”{}”][\/et_pb_divider][et_pb_text quote_border_color=”#003389″ _builder_version=”4.18.0″ text_font=”|600|||||||” text_text_color=”#323232″ link_text_color=”#3344dd” quote_font_size=”20px” header_font=”Roboto||||||||” header_text_color=”#323232″ max_width=”85%” module_alignment=”center” min_height=”88px” custom_margin=”-4px||15px|||” custom_padding=”0px||0px|||” hover_enabled=”0″ global_colors_info=”{}” header_3_font_size=”14px” sticky_enabled=”0″]<\/p>\n
In order to properly treat corneal infection and prevent sight loss, it is important to know the causative agent, which is usually either bacteria or fungi. However, diagnosing this is a challenge in many low and middle-income countries due to limited trained specialists and diagnostic laboratories.<\/p>\n
A new project by ICEH will develop and test a smartphone-based artificial intelligence (AI) tool for diagnosing corneal infections in Nepal. The study will identify AI models that are capable of accurately distinguishing the type of infection based on an image of the affected eye.<\/p>\n
The research will be conducted in 5 phases:<\/p>\n
1. Identifying alternative AI models of microbial keratitis (MK) for evaluation through a systematic review and meta-analysis
2. Independently comparing the diagnostic performance of these AI models, using our existing MK image collection (>2000 from 3 countries), identifying the most promising
3. Identifying the most suitable adapted smartphone-based camera system for taking corneal images for AI analysis
4. Evaluating image acquisition and AI model system combinations, to distinguish between fungal and bacterial keratitis
5. Evaluate implementation of the combined smartphone-based MK image acquisition and AI analysis system, to distinguish fungal keratitis and bacterial keratitis, in primary eye care centres<\/p>\n
The aim is to enable prompt referral and initiation of the correct treatment in low-resource rural areas, preserving eyes and vision for people with this painful condition.<\/p>\n
<\/p>\n
Acknowledgements<\/strong><\/p>\n We thank Velux Stiftung for funding this project and The Sagarmatha Choudhary Eye Hospital and Nepal Netra Jyoti Sangh for their partnership.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Artificial Intelligence for Corneal Infections\u00a0\u00a0In order to properly treat corneal infection and prevent sight loss, it is important to know the causative agent, which is usually either bacteria or fungi. However, diagnosing this is a challenge in many low and middle-income countries due to limited trained specialists and diagnostic laboratories. A new project by ICEH […]<\/p>\n","protected":false},"author":845,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-9877","page","type-page","status-publish","hentry"],"yoast_head":"\n