Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining

Applications of Deep Learning in Medical Engineering

Author(s): Sumit Kumar Jindal*, Sayak Banerjee, Ritayan Patra and Arin Paul

Pp: 68-99 (2)

DOI: 10.2174/9789815040401122030006

* (Excluding Mailing and Handling)

Abstract

As a result of considerable breakthroughs in the field of artificial intelligence, deep learning has achieved exceptional success in resolving issues.This work brings forth a historical overview of deep learning and neural networks and further discusses its applications in the domain of medical engineerings - such as detection of brain tumours, sleep apnea, arrhythmia detection, etc. One of the most important and mysterious organs of our body is the brain. Like any other organ, our brain may suffer from various life-threatening diseases like brain tumours which can be malignant or benign. Analysis of the brain MRI images by applying convolution neural networks or artificial neural networks can automate this process by classifying these images into various types of tumours. A faster and more effective method can be provided by this method for detecting the disease at a key stage from where recovery is possible. Sleep apnea is a sleeping disorder involving irregular breathing. The brain detects a sudden decrease in the level of oxygen and sends a signal to wake the person up while he is sleeping. Cardiac arrhythmia refers to a group of conditions that causes the heart to beat irregularly, too slowly, or too quickly, e.g., atrial fibrillation. Deep learning along with bio-medical signal and audio processing techniques on respiratory sound datasets and ECG datasets have huge potential in the detection of these diseases. Deep learning outperforms the existing detection algorithms and a good amount of effort on feature engineering, augmentation techniques, and building effective filters can get a high accuracy result.


Keywords: Artificial intelligence, Artificial neural networks, Atrial fibrillation, Automation, Audio processing, Brain tumours, Bio-medical signal processing, Cardiac arrythmia, Convolution neural networks, Deep learning, ECG, EEG, Feature engineering, Machine learning, MRI imaging, Neural networks, Optimization, Signal processing, Signal analysis, Sleep apnea.

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      • 13. app/Models/UserAccess/UserAccess.php:1266
      • 14. app/Http/Controllers/ChapterController.php:1518
      • 15. vendor/laravel/framework/src/Illuminate/Routing/Controller.php:54
      • 16. vendor/laravel/framework/src/Illuminate/Routing/ControllerDispatcher.php:43
      • 17. vendor/laravel/framework/src/Illuminate/Routing/Route.php:260
    • (select j.user_access_id,j.volume_id,j.user_id,j.from_ip,j.to_ip,j.type,j.track,"Trial Access" as access_base_text, CASE j.type WHEN 111 THEN true ELSE false END as terms_popup, "S" as content_download_type, null as restricted_user_access_key, null as restricted_user_access_type, CASE j.track WHEN 0 THEN false ELSE true END as tracksAccessByVolume,"chapter" as access_level, j.chapter_id from `user_access_chapter_trail` as `j` inner join `user_access_info` as `info` on `j`.`user_access_id` = `info`.`user_access_id` where ((j.from_ip <= 316870080 and j.to_ip >=316870080 )) and ((j.from_date <= 1740675800 and j.to_date >= 1740675800 and j.perpetual= 0) or (j.from_date is null and j.to_date is null and j.perpetual= 1)) and j.chapter_id = 17362) union (select j.user_access_id,j.volume_id,j.user_id,j.from_ip,j.to_ip,j.type,j.track,"Subscribed" as access_base_text, false as terms_popup, "S" as content_download_type, null as restricted_user_access_key, null as restricted_user_access_type, CASE j.track WHEN 0 THEN false ELSE true END as tracksAccessByVolume,"chapter" as access_level, j.chapter_id from `user_access_chapter_corporate` as `j` inner join `user_access_info` as `info` on `j`.`user_access_id` = `info`.`user_access_id` where ((j.from_ip <= 316870080 and j.to_ip >=316870080 )) and ((j.from_date <= 1740675800 and j.to_date >= 1740675800 and j.perpetual= 0) or (j.from_date is null and j.to_date is null and j.perpetual= 1)) and j.chapter_id = 17362) union (select j.user_access_id,j.volume_id,j.user_id,j.from_ip,j.to_ip,j.type,j.track,"Token Based Access" as access_base_text, false as terms_popup, "R" as content_download_type, j.uc_id as restricted_user_access_key, "v" as restricted_user_access_type, CASE j.track WHEN 0 THEN false ELSE true END as tracksAccessByVolume,"chapter" as access_level, j.chapter_id from `user_access_chapter_token` as `j` inner join `user_access_info` as `info` on `j`.`user_access_id` = `info`.`user_access_id` where ((j.from_ip <= 316870080 and j.to_ip >=316870080 )) and ((j.from_date <= 1740675800 and j.to_date >= 1740675800 and j.perpetual= 0) or (j.from_date is null and j.to_date is null and j.perpetual= 1)) and j.chapter_id = 17362)
      980μsalphaeurekaselec_live_10_06_2022UserAccess.php#1266
      Backtrace
      • 13. app/Models/UserAccess/UserAccess.php:1266
      • 14. app/Http/Controllers/ChapterController.php:1549
      • 15. vendor/laravel/framework/src/Illuminate/Routing/Controller.php:54
      • 16. vendor/laravel/framework/src/Illuminate/Routing/ControllerDispatcher.php:43
      • 17. vendor/laravel/framework/src/Illuminate/Routing/Route.php:260
    • select b.banner_link, b.banner_name, b.banner_script, b.banner_remarks, b.banner_file_name, b.banner_placement, bd.content_type, bd.content_id from `tbl_banner` as `b` inner join `tbl_banner_detail` as `bd` on `bd`.`banner_id` = `b`.`banner_id` inner join `users` as `u` on `u`.`id` = `b`.`updated_by` where `b`.`banner_ebook` = 1 and `bd`.`content_type` = 'B' and `bd`.`content_id` = 3373 and `b`.`banner_from_date` <= 1740675800 and `b`.`banner_to_date` >= 1740675800 and `b`.`banner_status` = 'A' order by `b`.`banner_id` desc
      1.47msalphaeurekaselec_live_10_06_2022Banner.php#95
      Bindings
      • 0: 1
      • 1: B
      • 2: 3373
      • 3: 1740675800
      • 4: 1740675800
      • 5: A
      Backtrace
      • 13. app/Models/Banner.php:95
      • 14. app/Http/helpers.php:404
      • 17. vendor/laravel/framework/src/Illuminate/Filesystem/Filesystem.php:124
      • 18. vendor/laravel/framework/src/Illuminate/View/Engines/PhpEngine.php:58
      • 19. vendor/laravel/framework/src/Illuminate/View/Engines/CompilerEngine.php:73
    • select count(*) as aggregate from `uc_cart_products` where cart_id='4300c78725864a3bd7bb1f603dbf128b'
      230μsalphaeurekaselec_live_10_06_2022Cart.php#271
      Backtrace
      • 15. app/Models/Cart.php:271
      • 16. view::layouts._header:260
      • 18. vendor/laravel/framework/src/Illuminate/Filesystem/Filesystem.php:124
      • 19. vendor/laravel/framework/src/Illuminate/View/Engines/PhpEngine.php:58
      • 20. vendor/laravel/framework/src/Illuminate/View/Engines/CompilerEngine.php:73
    App\Models\Keywords
    20Keywords.php#?
    App\Models\Chapter
    1Chapter.php#?
    App\Models\Ebook
    1Ebook.php#?
        _token
        2Zak3Z91TR5Q0OWUNCcjReQPAHrW36536xUqLeix
        uc_cart_id
        4300c78725864a3bd7bb1f603dbf128b
        _previous
        array:1 [ "url" => "https://alpha.eurekaselect.com/chapter/17362" ]
        _flash
        array:2 [ "old" => [] "new" => [] ]
        PHPDEBUGBAR_STACK_DATA
        []
        path_info
        /chapter/17362
        status_code
        200
        
        status_text
        OK
        format
        html
        content_type
        text/html; charset=UTF-8
        request_query
        []
        
        request_request
        []
        
        request_headers
        0 of 0
        array:16 [ "x-https" => array:1 [ 0 => "1" ] "host" => array:1 [ 0 => "alpha.eurekaselect.com" ] "priority" => array:1 [ 0 => "u=0, i" ] "accept-encoding" => array:1 [ 0 => "gzip, deflate, br, zstd" ] "sec-fetch-dest" => array:1 [ 0 => "document" ] "sec-fetch-user" => array:1 [ 0 => "?1" ] "sec-fetch-mode" => array:1 [ 0 => "navigate" ] "sec-fetch-site" => array:1 [ 0 => "none" ] "accept" => array:1 [ 0 => "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7" ] "user-agent" => array:1 [ 0 => "Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)" ] "upgrade-insecure-requests" => array:1 [ 0 => "1" ] "sec-ch-ua-platform" => array:1 [ 0 => ""Windows"" ] "sec-ch-ua-mobile" => array:1 [ 0 => "?0" ] "sec-ch-ua" => array:1 [ 0 => ""HeadlessChrome";v="129", "Not=A?Brand";v="8", "Chromium";v="129"" ] "cache-control" => array:1 [ 0 => "no-cache" ] "pragma" => array:1 [ 0 => "no-cache" ] ]
        request_cookies
        []
        
        response_headers
        0 of 0
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        session_attributes
        0 of 0
        array:5 [ "_token" => "2Zak3Z91TR5Q0OWUNCcjReQPAHrW36536xUqLeix" "uc_cart_id" => "4300c78725864a3bd7bb1f603dbf128b" "_previous" => array:1 [ "url" => "https://alpha.eurekaselect.com/chapter/17362" ] "_flash" => array:2 [ "old" => [] "new" => [] ] "PHPDEBUGBAR_STACK_DATA" => [] ]
        ClearShow all
        Date ↕MethodURLData
        #12025-02-27 17:03:20GET/chapter/173621121922